We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Despite the excitement surrounding generative AI, the data shows that scientific research is still powered primarily by ...

From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...

Researchers at Thomas Jefferson University have developed an automated machine learning (AutoML) model that can accurately ...

LifeTracer is not a universal life detector. Rather, it provides a foundation for interpreting complex organic mixtures. The Bennu findings remind us that life-friendly chemistry may be widespread ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

A new research paper featured on the cover of Volume 17, Issue 11 of Aging-US was published on October 30, 2025, titled “SAMP-Score: a morphology-based machine learning classification method for ...

An AI-driven computational toolkit, Gcoupler, integrates ligand design, statistical modeling, and graph neural networks to predict endogenous metabolites that allosterically modulate the GPCR–Gα ...

Weeds pose the most persistent and costly threat to crop production in Canada, driving widespread herbicide use and accelerating the rise of herbicide-resistant species ...

Insurance companies aren't experimenting with AI. They're deploying it at scale across three critical functions that directly ...

In a study published in Frontiers in Science, scientists from Purdue University and the Georgia Institute of Technology ...