Building AI You Can Understand
A new cognitive architecture aims to move beyond opaque machine learning models by grounding AI reasoning in foundational principles of human cognition.
A new cognitive architecture aims to move beyond opaque machine learning models by grounding AI reasoning in foundational principles of human cognition.

Researchers have developed a complete robotic system that combines advanced perception and a novel soft-rigid gripper to gently and reliably harvest ripe tomatoes.
A philosophical exploration proposes that AI safety lies not in hardcoding values, but in designing systems capable of emergent values through embodied interaction.
Researchers have developed a novel method to distinguish humans from increasingly sophisticated AI bots by exploiting subtle differences in visual motion perception.
New research explores whether artificial intelligence will exacerbate existing differences in human cognitive ability or act as a tool to reduce them.

Researchers have developed a system that allows robots to learn the best moments to initiate conversations with people, leading to more natural and engaging interactions.

A new agentic framework combines physics-informed machine learning with adaptive sampling to automate complex scientific computing tasks.

A new approach uses teams of artificial intelligence agents to automatically discover effective strategies for solving notoriously difficult computational problems.

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.