Anyone exploring technological advances in artificial intelligence (AI) will inevitably encounter spiking neural networks (SNNs) — the next step toward energy‑efficient real‑time AI. The difference ...

This valuable study provides a practical computational framework for inferring latent neural states directly from calcium fluorescence recordings, bypassing the traditional need for a separate spike ...

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 employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

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, ...

Parth is a technology analyst and writer specializing in the comprehensive review and feature exploration of the Android ecosystem. His work is distinguished by its meticulous focus on flagship ...

Synopsys has launched a new neural processing unit (NPU) intellectual property (IP) core and toolchain that delivers 3,500 TOPS to support the performance requirements of increasingly complex neural ...

Nvidia’s latest pitch for the future of graphics is not about more polygons or higher memory bandwidth, it is about teaching ...

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 ...