Q&A: How mathematics can reveal the depth of deep learning AI

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms ...
Business Wire

Data Science And Deep Learning Application Leaders Form GPU Open Analytics Initiative

SAN JOSE, Calif.--(BUSINESS WIRE)--Continuum Analytics, H2O.ai, and MapD Technologies have announced the formation of the GPU Open Analytics Initiative (GOAI) to create common data frameworks enabling ...
eWeek

Machine Learning vs. Deep Learning

Machine learning and deep learning are both core technologies of artificial intelligence. Yet there are key differences between them. Written by eWEEK content and product recommendations are ...
Analytics Insight

Best GPU for AI & Deep Learning in 2025

Overview: The proper GPU accelerates AI workloads, neural network training, and complex computations.Look for high CUDA core ...
Forbes

What Is Deep Learning AI?

Editorial Note: Forbes Advisor may earn a commission on sales made from partner links on this page, but that doesn't affect our editors' opinions or evaluations. There is a lot of buzz around ...
eWeek

Neural Networks vs. Deep Learning

Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...
Hackaday

Here’s Why GPUs Are Deep Learning’s Best Friend

If you have a curiosity about how fancy graphics cards actually work, and why they are so well-suited to AI-type applications, then take a few minutes to read [Tim Dettmers] explain why this is so. It ...

Topology-aware deep learning model enhances EEG-based motor imagery decoding

Electroencephalography (EEG) is a fascinating noninvasive technique that measures and records the brain's electrical activity. It detects small electrical signals produced when neurons in the brain ...
Science Daily

Deep learning for new protein design

Deep learning methods have been used to augment existing energy-based physical models in 'do novo' or from-scratch computational protein design, resulting in a 10-fold increase in success rates ...