Dropout training is a relatively new algorithm which appears to be highly effective for improving the quality of neural network predictions. It's not yet widely implemented in neural network API ...

James McCaffrey explains the common neural network training technique known as the back-propagation algorithm.

Facilitating the reuse of trained neural networksBOSTON, MA, July 10, 2025 (GLOBE NEWSWIRE) -- – Object Management Group® ...

Their newly proposed, visual system-inspired computational techniques, dubbed all-topographic neural networks (All-TNNs), are introduced in a paper published in Nature Human Behaviour.

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

AI vision models have improved dramatically over the past decade. Yet these gains have led to neural networks which, though effective, don’t share many characteristics with human vision. For example, ...

On the hardware front, Baidu is collaborating with Intel on the research and development of Nervana Neural Network Processor for Training (NNP-T), a hardware accelerator optimized for deep learning.

This is because neural networks require extensive training for their inputs (such as pixels in an image) to produce the appropriate output (such as a description of the image).