Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models that are deeply aligned with their specific data domains ...
News-Medical.Net

Researchers develop versatile machine learning tool to automate complex clinical diagnostics

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.

Automated CT scan analysis could fast-track clinical assessments

A research team has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease. Scientists used their tool, named Merlin, to assess 3D ...
Northwestern's McCormick School of Engineering

Multi-Institution Team Wins Two Awards at AAAI-26 Workshops

First author Canyu Chen led a multi-institution research team in developing a scalable approach to training AI agents without sacrificing users’ data privacy.
Frontiers

Challenges in Integrating Heterogeneous Biomedical Data for Precision Medicine: AI Models and Applications

This Research Topic focuses on using artificial intelligence (AI) to combine and analyze diverse biomedical data types to improve the performance and ...
Tech Xplore

New ensemble AI model enhances cyber intrusion detection with high accuracy

A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...
AZoOptics

AI-Enhanced Optical Spectroscopy for On-Line Food Quality Monitoring

AI-enhanced optical spectroscopy revolutionizes food quality monitoring with rapid, non-destructive analysis, ensuring safety and reducing waste in production.
InfoQ

Google Publishes Scaling Principles for Agentic Architectures

Researchers from Google and MIT published a paper describing a predictive framework for scaling multi-agent systems. The framework shows that there is a tool-coordination trade-off and it can be used ...
IEEE

Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function

Abstract: Multi-label emotion classification (MLEC) for low-resource languages like Arabic faces significant challenges due to class imbalance and label correlations, particularly in accurately ...

Mohammad Hossain Builds AI-Driven Decision Support Using Business Analytics and Engineering Intelligence for Markets

This research initiative highlights practical AI and business analytics for decision support across infrastructure, ...
EE World Online

The difference between physical AI and machine learning in power electronics

Physical artificial intelligence (PAI) is the application of AI and machine learning (ML) algorithms to enable autonomous ...
IEEE

Learning in Imperfect Environments: Multi-Label Classification of Non-Functional Requirements under Long-Tailed Distribution

Abstract: Automatically identifying and classifying nonfunctional requirements (NFRs) such as reliability and security from software requirements is one of the most active research topics in the field ...