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 ...

The search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a ...

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

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 ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

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 ...