But neural networks have a big problem: they're really complicated. They're so complex, in fact, that researchers have often struggled to explain precisely why they make specific decisions.

Spiking neural networks (SNNs) are a type of neural network based around changes to an existing state. Spike-based approaches seek to more closely model the dynamics of learning in biological brains, ...

INT8 provides better performance with comparable precision than floating point for AI inference. But when INT8 is unable to meet the desired performance with limited resources, INT4 optimization is ...

Neuromorphic computing, as a novel approach to processing information by mimicking biological neural networks, has gradually demonstrated significant ...

A biomimicking neural network housed in a microchip could lead to faster and more efficient applications of artificial intelligence. This is the claim of researchers at KAUST in Saudi Arabia whose ...

Neural networks process vast amounts of information to help create an understanding of what's already right in front of you. People think the key to understanding neural networks is calculus, ...

A new neural network process has designed wireless chips that can outperform existing ones. This convolutional neural network analyzes the desired chip properties then designs backward. Much of AI ...