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.

In the ever-evolving landscape of artificial intelligence, there is a growing interest in leveraging insights from neuroscience to create more ...

In a new study, Chinese researchers tested whether monitoring passengers’ brain activity could help self-driving systems make ...

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AI bots told to act as trading agents in simulated markets engaged in pervasive collusion, raising new questions about how financial regulators have previously addressed this tech.

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...

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 ...

You might have seen headlines sounding the alarm about the safety of an emerging technology called agentic AI.

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to language for AI because it’s relatively easy to learn and has a massive library of ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...