Enterprise AI workloads require infrastructure designed for large-scale data processing and distributed computing.

By bringing the training of ML models to users, health systems can advance their AI ambitions while maintaining data security ...

In today’s fast-changing data landscape, having a strong data system and advanced analytical tools is key to getting valuable insights and staying ahead of the competition. The data lakehouse ...

I’ve been flying multispectral missions for a few years now, and the biggest surprise of these systems is how much processing ...

For R&D leaders evaluating AI investments, I’d offer one piece of advice: Before spending more on models, look hard at your ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines. By Daniel Fusch Neel Somani, a ...

Purdue’s innovative Master of Science in Data Science (MSDS) is an accessible, skills-focused master’s designed to meet the needs of professionals who have some background in data science and want to ...

Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...

The use of data analytics in sport, pioneered by the Oakland Athletics Major League Baseball team, and depicted in the movie “Moneyball”, has fundamentally changed how players are scouted, valued, and ...