Science

Researchers have developed a new technique for creating soft robotic actuators with programmable movement by strategically cutting patterns into porous foam materials.

This review explores the evolving landscape of safe learning techniques enabling robots to perform intricate, contact-rich tasks without causing harm or damage.

As artificial intelligence reshapes digital forensics, ensuring transparency and accountability requires a shift towards open standards and human-readable documentation.

Researchers are pioneering a rapid, iterative approach to working with generative AI that prioritizes critical reflection alongside creative exploration.

A new AI system translates complex numerical forecasts into human-understandable reports, complete with explanations and contextual awareness.

As generative AI rapidly transforms the landscape of work and creativity, a fundamental rethinking of economic and ethical frameworks is now essential.

New research demonstrates a reinforcement learning approach enabling multiple robots to coordinate exploration and maintain formation while navigating complex environments.

A new system intelligently navigates the vast landscape of scholarly literature to reveal patterns and insights often missed by traditional search methods.

New research explores how microphones can be used to accurately identify different types of physical touch applied to robotic surfaces.

This article explores how integrating artificial intelligence agents into established research workflows can help software engineers define more relevant and impactful research questions.