Science

Researchers have developed a new framework enabling humanoid robots to interpret natural language commands and translate them into stable, physically realistic movements.

As AI agents increasingly write our code, ensuring that their output matches our intentions is becoming a critical challenge.

Researchers have developed a new framework that distills an agent’s creative process into reusable templates, significantly improving the efficiency and quality of text-to-image creation.

As we increasingly rely on artificial intelligence to make sense of complex information, a critical question arises: are we truly enhancing our insights, or subtly allowing algorithms to shape our perspectives?

A new study explores how intelligent agents can help ensure fairness in early-onset colorectal cancer screening.

Researchers have unveiled a comprehensive collection of human demonstrations designed to help robots master complex, contact-rich manipulation tasks.

A new framework leverages real-to-sim transfer and lightweight machine learning to significantly improve the efficiency and reliability of remote manipulation tasks.

A new research protocol allows for automated specification search in empirical economics while maintaining full transparency and auditability.

New research reveals how incorporating behavioral economics into multi-agent AI systems alters strategic interactions and challenges traditional game theory assumptions.

Subtle changes to the mechanical design of handheld grippers used in human demonstrations can dramatically improve the quality of robot training for complex manipulation tasks.