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 ...

An article recently published in Nature proposes a new way to evaluate data quality for artificial intelligence used in healthcare. Several documentation efforts and frameworks already exist to ...

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

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 ...

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

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 ...

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 ...

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