Speech recognition, handwriting recognition, face recognition: just a few of the many tasks that we as humans are able to quickly solve but which present an ever increasing challenge to computer ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

It’s been ten years since AlexNet, a deep learning convolutional neural network (CNN) model running on GPUs, displaced more traditional vision processing algorithms to win the ImageNet Large Scale ...

Earth Scientists have used machine learning for at least three decades and the applications span is large, from remote sensing to analysis of well log data, among many others. Although machine ...

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential across disciplines. These ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Multimodal sensing in physical AI (PAI), sometimes called embodied AI, is the ability for AI to fuse diverse sensory inputs, ...

Previously met with skepticism, AI won scientists a Nobel Prize for Chemistry in 2024 after they used it to solve the protein folding and design problem, and it has now been adopted by biologists ...

Neural networks are the backbone of algorithms that predict consumer demand, estimate freight arrival time, and more. At a high level, they're computing systems loosely inspired by the biological ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...