Huisheng Liu Examines Multi-Cloud MLOps as a Path to More Reliable Commercial AI Services

A multi-cloud MLOps framework improves AI service reliability through automated deployment, canary releases, and ...
Tech Xplore

New federated learning algorithm enables private, robust, and fast AI development

Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...

Fuzheng Liu Examines Transformer-XL Modeling of E-Commerce User Behavior and Real-Time Behavioral Analysis

XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
The Next Web

Entire launches a distributed Git network built for AI coding agents

Entire, founded by former GitHub CEO Thomas Dohmke, has launched a preview of a distributed Git network that mirrors GitHub repos across regions for AI agents.
Blockonomi

5 Leading AI Cryptocurrency Projects Shaping 2026: TAO, NEAR, and RENDER in Focus

Leading AI Cryptocurrency Tokens for 2025. The intersection of artificial intelligence and blockchain technology is ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
Yonhap News Agency on MSN

Int'l conference on machine learning

Participants wait to enter this year's International Conference on Machine Learning, a premier international forum in machine ...
BMJ Open

Implementation determinants of a planned machine learning-enabled surgical scheduling system in a high-volume orthopaedic centre in Canada: qualitative findin…

Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...
IEEE

L3DML: Facilitating Geo-Distributed Machine Learning in Network Layer

Abstract: Geo-Distributed Machine Learning (GDML) aims to train large-scale machine learning models across geographically dispersed datacenters. However, the performance of GDML systems is constrained ...
IEEE

From Federated to Fog Learning: Distributed Machine Learning over Heterogeneous Wireless Networks

Abstract: Machine learning (ML) tasks are becoming ubiquitous in today's network applications. Federated learning has emerged recently as a technique for training ML models at the network edge by ...