As proposed and demonstrated by the Los Alamos team, the architectures and techniques proposed to mitigate or altogether ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language translation. A quantum counterpart—known as a quantum convolutional neural ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

MicroCloud Hologram Inc. has announced the creation of a noise-resistant Deep Quantum Neural Network (DQNN) architecture, which aims to advance quantum computing and enhance the efficiency of quantum ...

In recent years, artificial intelligence technologies, especially the machine learning algorithms, have made great strides. These technologies have enabled unprecedented efficiency in tasks such as ...

Core to the approach is what the companies call a one-step simplified LBM, or OSSLBM, framework. The method uses a hybrid ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research I have used a phenomenon called “quantum tunnelling” to ...