Vice President of AI & Quantum Computing, Paul Smith-Goodson gives his analysis of quantum machine learning models and IonQ's strategy to make it a reality.

Foundation Models are essentially large-scale machine learning models pre-trained on massive datasets. Unlike traditional ML models, these are designed to be versatile and can be fine-tuned to ...

Recent advances in machine learning have shown that deep neural networks (DNNs) can provide powerful and flexible models of neural sensory processing. In the auditory system, standard linear-nonlinear ...

Machine-learning model can reliably predict cognitive performance based on lifestyle indicators. Story by Diana Yates • 18m. A new study offers insight into the health and lifestyle indicators ...

Researchers have developed a technique that significantly improves the performance of large language models without ...

Machine learning model helps identify patients at risk of postpartum depression Date: May 19, 2025 Source: Mass General Brigham Summary: Postpartum depression (PPD) affects up to 15 percent of ...

New research pioneered by Clapp and other Mass General Brigham researchers aims to detect the risk of postpartum depression earlier, starting in the delivery room after the baby is born. They’ve ...

Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the ...

CHARTwatch, a machine learning model, shows promise in reducing patient mortality and improving outcomes in hospital settings, according to new CMAJ study. Study: Clinical evaluation of a machine ...

A machine learning model using random forest algorithms outperforms neural networks and traditional regression in predicting tsunami early warnings for Tofino, B.C., but all models benefit from ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, molecules, and materials.