Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a ...

Researchers report building photonic computing chips that use light pulses to train spiking neural networks on robotic-control-style benchmark tasks, aiming to shift more of the learning workload from ...

What if the thermal noise that hinders the efficiency of both classical and quantum computers could, instead, be used as a ...

Lab-grown mini-brains learned to play video games using electrical signals, improving from 4.5% to 46% success in AI balance tests.

A Queen’s research team has developed a new way to train AI systems so they focus on the bigger picture instead of specific, optimized data.

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 team of researchers at the University of California, Los Angeles (UCLA) has introduced a novel framework for monitoring ...

A two-chip photonic neuromorphic system performs real time spiking reinforcement learning using only light, achieving GPU-class energy efficiency.

This video explores how neural networks evolved from early ideas about the brain into the foundation of modern deep learning. From Rosenblatt’s perceptron to GPUs and backpropagation, it traces the ...

“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 ...

Neural Concept is helping launch products at 2X the speed. It does this by capturing past knowledge into AI-based ...