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

Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

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 ...

A Performant Side-channel-Resistant RISC-V Core Securing Edge AI Inference” was published by researchers at Northeastern ...

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...

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

More than two decades ago, neural networks were widely seen as the next generation of computing, one that would finally allow computers to think for themselves. Now, the ideas around the technology, ...

“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 ...

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

A team of researchers at Penn State have devised a new, streamlined approach to designing metasurfaces, a class of engineered ...