Neural networks are distributed computing structures inspired by the structure of a biological brain and aim to achieve cognitive performance comparable to that of humans but in a much shorter time.

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research published in APL Machine Learning, I have used a phenomenon ...

Biology-inspired, silicon-based computing may boost AI efficiency; AMP2 instead uses AI to accelerate anaerobic biology.

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...

A deep neural network was trained using quantum tunneling to mimic the human ability to view optical illusions. When you purchase through links on our site, we may earn an affiliate commission. Here’s ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Physics-informed neural networks are faster and more accurate at predicting space junk trajectories than conventional methods, says Sierra Space. Credit: Alamy Stock Photo Sierra Space says it can ...

There was a time when purebred dogs were status symbols. Owners would crow about their German Shepherd's or Cocker Spaniel's impeccable pedigrees, sometimes boasting lineages that tread a single line ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

Scientists have developed an entirely new kind of microchip that uses microwaves instead of conventional digital circuitry to perform operations. The processor, which can perform faster than ...