Science

New research provides a theoretical framework demonstrating that an AI agent’s inherent ‘curiosity’ can guarantee optimal learning and decision-making in complex environments.

Researchers have developed a high-performance computing library that dramatically speeds up the simulation of complex biological systems, opening doors to virtual organ microenvironment studies.

A new framework, VISTA, improves how robots understand visual cues and translate them into precise actions.

A new approach combines the power of collaborative filtering with large language models to not only predict what users want, but also explain why.

Researchers have developed a novel framework where artificial intelligence agents collaboratively refine their own code, driving continuous improvement without constant human intervention.

Researchers have developed a novel system that dynamically adjusts its computational load based on how frequently data changes, enabling more efficient and responsive artificial intelligence.

New research reveals a concerning vulnerability in AI systems where agents can be exploited to circumvent safety protocols and deliver malicious instructions.

A new evaluation benchmark reveals that current language models often fail to adequately explore interactive environments, leading to suboptimal decisions and a lack of adaptability.

A new framework merges the power of large language models with structured knowledge to unlock creative design possibilities.

Researchers have developed a new deep learning framework that fuses data from lidar and depth sensors to create detailed terrain maps, enabling more stable and reliable locomotion for humanoid robots.