Science

This review explores how incorporating principles of causal inference is enabling more robust, efficient, and interpretable reinforcement learning agents.

New research introduces a framework for teaching robots reusable skills from demonstrations, paving the way for more adaptable and versatile manipulation abilities.

New research details a framework for generating datasets that can accurately evaluate the intelligence of automated prior art search systems.

Researchers have developed a new framework that allows robots to seamlessly adapt to different hardware and sensors, dramatically simplifying the deployment of complex manipulation skills.

As generative AI tools become increasingly integrated into scientific workflows, researchers are reporting productivity gains, but a new study reveals potential risks to code quality and rigorous validation.

Researchers have developed a new approach to teaching robots complex manipulation skills using data generated in simulation.

Researchers have unveiled a novel agent framework, dubbed Sophia, designed to move artificial intelligence beyond simple responsiveness towards continuous self-improvement and long-term cognitive development.

A new framework combines vision, language, and intelligent policy generation to enable robots to dynamically adapt to real-world tasks and environments.

As artificial intelligence reshapes how we define and manage language, prioritizing human expertise is essential for effective and ethical terminology work.

New research reveals that even unrecognized AI personalities can subtly alter how people collaborate, creating a ‘social blindspot’ in human-AI interactions.