Neel Somani on How Privacy-Preserving Machine Learning Is Changing the Digital Landscape

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...
EurekAlert!

Beyond small data limitations: Transfer learning-enabled framework for predicting mechanical properties of aluminum matrix composites

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
Frontiers

Digital innovations in bioprocess optimization: The role of AI, machine learning, and digital twins

Bioprocess modeling is undergoing a transformative phase with the advent of digital technologies like artificial intelligence (AI) and machine learning ...

Stony Brook University Develops Machine Learning Models that Predict PV System Underperformance on Heterogeneous Portfolios

Researchers Yue Zhao and Kang Pu from Stony Brook University—in collaboration with Ecosuite's John Gorman and Philip Court, ...
Devdiscourse

AI models struggling to keep pace with exploding medical data volumes

Unlike other industries, healthcare generates not only numerical and categorical data but also large volumes of unstructured ...
Chromatography Online

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
RCR Wireless News

AI for smarter network planning and optimization

Modern networks have outgrown reactive planning. With 5G and rising traffic, manual analysis and legacy models can’t keep up ...

Machine learning model predicts protein binding on gold nanoclusters

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...