Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, photonic circuits typically behave linearly, limiting the flexible ...

Studies of quantum computing and its overlap with photonics have gathered pace in recent years, with groups such as the Danish PhotoQ consortium investigating the development of photonic quantum ...

Principal Research Fellow at AI and Cyber Futures Institute, Charles Sturt University Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance.

TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench—a powerful toolkit that enables data scientists to significantly improve ML ...

Measurements at the Large Hadron Collider have been stymied by one of the most central phenomena of the quantum world. But now, a young researcher has championed a new method to solve the problem ...

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 ...