Science

Researchers are developing systems that allow humans to seamlessly coordinate with multiple robots using natural communication and shared understanding of the physical world.

A new approach leverages AI personas modeled on expert reasoning to deliver explanations that adapt to individual understanding and build trust in complex scientific domains.

Researchers have developed a new framework that allows autonomous agents to efficiently explore and solve complex coding problems in scientific domains.

New research reveals distinct patterns in how humans and artificial intelligence work together, impacting both efficiency and critical thinking.

A new framework leverages artificial intelligence to create RF systems that learn, adapt, and optimize their performance in real-time.

A new framework combines vision and control to enable robotic arms – blending rigid and soft components – to reliably grasp objects in complex, real-world environments.

Artificial intelligence is rapidly transforming how businesses iterate and improve, moving beyond theory to fuel practical experimentation.

New research details a framework for multi-robot teams to dynamically adapt and efficiently complete tasks in uncertain environments.

This review explores how Active Inference, implemented through reactive message passing, offers a principled architecture for creating robust and adaptable physical AI agents.

Researchers have developed a framework that combines the reasoning power of large AI models with the efficiency of smaller, edge-based systems to enhance multi-robot coordination and exploration.