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 ...
University of Illinois professor Klara Nahrstedt received $275,000 from the National Science Foundation to develop streaming technology for AI-generated neural video content. Her research focuses on ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...
Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
“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 ...
Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
The Stellar P3E is the first automotive microcontroller to ship with ST’s Neural-ART Accelerator. It offers a 20x to 30x improvement in inference operations compared to a similar MCU without a ...
Future Market Insights (FMI) projects the Neural Processors Market to grow from USD 176 million in 2025 to USD 1,010 million by 2035, advancing at a 19.1% CAGR. This surge is being driven by the ...
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 ...
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