Neuromorphic Chips and 'Brain‑Like' Computing: How Next‑Gen Chips May Change Phones, Robots, and IoT Devices

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...
News-Medical.Net on MSN

NSLLMs: Bridging neuroscience and LLMs for efficient, interpretable AI systems

Large language models (LLMs) have become crucial tools in the pursuit of artificial general intelligence (AGI).
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Harvard Business Review

Why Leadership Training Fails—and What to Do About It

Companies spend billions on programs that don’t pay off. Here’s how to fix that. by Michael Beer, Magnus Finnström and Derek Schrader Corporations are victims of the great training robbery. American ...
IEEE

Joint Sparse Bayesian Learning for Channel Estimation in ISAC

Abstract: In this letter, we investigate channel estimation in integrated sensing and communication and propose a joint sparse Bayesian learning (JSBL) algorithm for the estimation of sensing and ...
eLife

Retrosplenial cortex enables context-dependent goal-directed sensorimotor transformation

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.