The exponential growth of network complexity, traffic volume and security demands is challenging the scalability of classical automation frameworks. Artificial intelligence (AI) has improved network ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

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 ...

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 ...

This post may contain links from our sponsors and affiliates, and Flywheel Publishing may receive compensation for actions taken through them. But if that tide continues rising, or once commercially ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Quantum computing promises to disrupt entire industries because it leverages the rules of quantum physics to perform calculations in fundamentally new ways. Unlike traditional computers that process ...

A number of voices question when quantum computing technologies will deliver true business value, but IT and networking giant Cisco says that through new networking application demos for classical use ...

Quantum-inspired Leaky Integrate-and-Fire (QLIF) neurons for PyTorch, adaptive thresholds, dynamic spike probabilities, synaptic plasticity, neuromodulation, and optional qubit-based spike decisions.

Abstract: This work explores the integration of quantum computing within a classical Convolutional Neural Network (CNN) framework, leveraging a VGG16 model enhanced with a quantum Convolutional Neural ...