Nature

AI models were given four weeks of therapy: the results worried researchers

Chatbots put through psychotherapy report trauma and abuse. Authors say models are doing more than role play, but researchers ...

AI’s Memorization Crisis

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...
Frontiers

Modeling, Machine Learning, Bioinformatics and Multi-omics Data in Soil Science

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
Frontiers

Improving Machine Learning for Water Resources Through Scientific Knowledge Integration

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...
EurekAlert!

Machine learning revolutionizes design of green solvents for carbon capture: a new era for ionic liquid development

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...
United States Army

Army establishes new AI, machine learning career path for officers

The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning ...
IEEE

PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity

Abstract: The vulnerabilities and security issues of industrial Cyber-Physical Systems (CPSs), such as Intrusion Detection Systems (IDSs), have significantly increased due to the rapid integration of ...
IEEE

Learning-Based Temporal Sequence of Constrained Handling Selection for Constrained Multi-objective Evolutionary Optimization

Abstract: Constraint-handling techniques and genetic operators are two crucial components in constrained multi-objective evolutionary algorithms (CMOEAs). Recent research in most of CMOEAs has ...