Science

A new system combines advanced humanoid robots with real-time perception and reasoning to autonomously monitor and respond to hazards in industrial facilities.

Researchers have developed a framework for identifying causal relationships from complex, interdependent data, paving the way for deeper insights in fields like genomics.

A new approach leverages causal inference to pinpoint the key design parameters that truly impact analog circuit behavior.

New research demonstrates a coordinated navigation and printing system for mobile additive manufacturing robots, enabling continuous fabrication even over challenging terrain.

New research reveals that even advanced artificial intelligence systems struggle with the nuances of effective communication, hindering their ability to collaborate on complex tasks.

Researchers are increasingly leveraging artificial intelligence to accelerate discovery, but a systematic approach to integrating AI into the research process is often lacking.

A new system dramatically reduces the need for real-world data collection by generating large, realistic datasets for training robots to manipulate deformable objects like cloth and rope.

A new framework enables large language models to dynamically adapt to specific tasks by learning from human feedback, creating a collaborative sensemaking process.

A new framework dramatically improves data efficiency in robotic manipulation by breaking down complex tasks into reusable, independent factors.

A new benchmark, ARC-AGI-3, pushes AI systems beyond rote learning to assess their ability to efficiently acquire and generalize skills in dynamic, interactive environments.