Machine-learning-based predictions intelligently analyse complex sensor data to enhance equipment maintenance and reliability.

Research indicates that a mother’s diet before conception may influence her child’s brain development and behavior.

A*STAR researchers develop machine learning models that quickly and accurately simulate chemical reactions involving complex liquid interactions.

Understanding the psychological traits of flexitarians reveal the different motivations for adopting a flexitarian diet.

As the immune system ages, our susceptibility to conditions such as cancer increases, prompting researchers to develop advanced experimental models to study these pathways.

Advanced photonic processors boost machine learning efficiency by handling vast data streams in parallel, with potential benefits for enhanced patient monitoring and cloud computing.

Chemicals in everyday products may impact babies’ metabolic health, potentially leading to increased belly fat at birth.

Researchers find that pre-training AI models on a global scale boosts their performance in machine learning tasks, particularly in scenarios with limited training data.

A newly discovered antibiotic compound found in local soil can potentially combat some of the world’s toughest drug-resistant bacteria.

A robust machine learning approach to predict and optimise fuel consumption in ships is critical to practically enhance maritime environmental sustainability.