Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Abstract: In complex and dynamic environments, achieving autonomous decision-making and control of agent remains a challenging task. Traditional reinforcement learning algorithms often struggle to ...

A new career path for Army officers that focuses on AI further cements the service’s shift toward cutting-edge technology and ...

Can autonomous car racing challenge F1? A2RL’s 150mph AI battles are getting closer to human drivers, bolder, and more ...

The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), ...

ROS System, Hospital Drug Delivery Robot, Autonomous Localization, Path Planning, Navigation Simulation Cheng, B. and Zhang, B.Y. (2025) Research on Autonomous Localization and Navigation Simulation ...

Less than a year ago, it seemed like that day when generative AI would bring about a new era of supply chain autonomy—one where AI could adeptly make all the inventory and logistics decisions—was ...

Nvidia announced new infrastructure and AI models on Monday as it works to build the backbone technology for physical AI, including robots and autonomous vehicles that can perceive and interact with ...

The new reinforcement learning system lets large language models challenge and improve themselves using real-world data instead of curated training sets. Meta researchers have unveiled a new ...