Science

A new framework enables robots to learn long-duration manipulation skills from just a single demonstration, paving the way for more adaptable and user-friendly robotic systems.

New research reveals that transformer models can develop abstract reasoning skills by learning symbolic strategies, even without explicit training on pre-defined concepts.

Researchers are developing richer ways for artificial intelligence to understand indoor environments, enabling more effective task planning and interaction.

New research reveals that fundamental mathematical constraints – Gödel’s incompleteness and the chaotic nature of dynamical systems – impose inherent limits on the predictive capabilities of even the most advanced artificial intelligence.

A new framework combines imitation learning and reinforcement learning to empower robots to autonomously generate training data, leading to more robust and efficient manipulation skills.

As artificial intelligence rapidly reshapes societies, ensuring its development respects cultural identities and promotes equitable progress is becoming critically important.

Researchers have created a surprisingly lifelike robotic replica of the animated character Olaf, prioritizing realistic movement and believability over purely functional robotic performance.

A new open-source platform, TIB AIssistant, aims to empower researchers by seamlessly integrating artificial intelligence throughout the entire research process.

As smart homes become increasingly sensor-rich, effectively managing the resulting data is crucial for a seamless and trustworthy user experience.

As generative AI reshapes education, a new framework is needed to empower learners and educators to actively shape these technologies, not simply be shaped by them.