Abstract: Hierarchical Federated Learning (HFL) has emerged as a promising paradigm for distributed machine learning in edge computing environments. By introducing intermediate edge servers between ...

Modern-day LLMs are "fiction machines," designed not to be truthful but to make sense. What can we expect from these machines, and what are their limitations?

We are trying to fix health care as if it were complicated. In reality, health care is complex.

New digital platform combines regulatory intelligence, food safety analytics and AI-driven risk detection With SGS ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

Research by Ranga Raya Reddy Eragamreddy reveals how AI orchestration improved EV energy platform workflows and reduced costs.

Discover how a new AI system is revolutionizing energy management by merging machine learning and mathematical programming. This innovative approach not only boosts prediction accuracy but also ...

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast consumption, detect faults, and optimize system performance in real-time. What was ...

Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink bandwidth is the main ...

The field of medicine and medical imaging (X-rays, MRIs, CT scans, etc.) is rich in data, creating fertile ground for Artificial Intelligence (AI). Machine learning models, particularly deep neural ...