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 ...

Researchers have unveiled a new generation of photonic computing chips capable of performing real‑time learning and decision‑making using only light-based processes. Photonic chips deliver real‑time ...

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 ...

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 ...

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 ...

Researchers have built new photonic computing chips that allow neural networks to learn using ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...

Emergence of new applications and use cases: Neural networks are being applied to an increasingly diverse range of applications, including computer vision, natural language processing, fraud detection ...

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 ...