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

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...

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.

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

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

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

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

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

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...

OpenAI says prompt injections will always be a risk for AI browsers with agentic capabilities, like Atlas. But the firm is ...