Machine Learning Articles

Ellen Glover

Updated on February 19, 2025

Distillation condenses large AI models into smaller, more efficient ones — cutting down costs and complexity while preserving all the advanced capabilities.

Mamdouh Refaat

Updated on February 12, 2025

Overfitting is when a machine learning model performs well with its training data but performs poorly with new data. Here’s an in-depth review of what can lead to overfitting, how it differs from underfitting and methods for detecting and avoiding it.

Juan D. Ramirez

Updated on February 04, 2025

The superfast, superefficient Chinese model marks a paradigm shift in AI development.

Shanti Greene

Updated on January 28, 2025

You can use partial least squares regression to analyze relationships among multiple variables in a data set. Here’s what to know.

Simon Bailey and Tord Strømdal

Updated on January 27, 2025

AI-powered drones have the potential to make it faster and safer to remove mines. Our experts explain how it works and why the future may not be that far away.   

Minghong Fang

Updated on January 24, 2025

Our expert presents solutions to poisoning attacks in distributed machine learning, ensuring that privacy and efficiency can go hand-in-hand.

Nick Sanchez

Updated on January 23, 2025

AI hallucinations are thought to be a prevalent issue in tech, but what if it’s just user error? Our expert explains how to spot the difference.

Sijie Guo

Updated on January 22, 2025

This year, the way we work with data is poised to go from fragmented origins to AI-driven unity.

Ali Chaudhry, Adi Andrei and Julius Cerniauskas

Updated on January 15, 2025

The hype around AI didn’t die down in 2024, so what will this new year hold?

Erik Brown

Updated on December 19, 2024

Synthetic data has the potential to speed up and improve the building of AI models. Here’s why it may overshadow real data models by 2030.