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

In this video, we will understand forward propagation and backward propagation. Forward propagation and backward propagation ...

At SIGGRAPH 2025 today, Arm pulled the wraps off Neural Super Sampling (NSS), its first AI-driven upscaling technology designed for mobile GPUs. It's the debut application of "Arm neural 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 ...

What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.

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 ...

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, ...

The best way to understand neural networks is to build one for yourself. Let's get started with creating and training a neural network in Java. Artificial neural networks are a form of deep learning ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...