Classiq 1.0 is designed for enterprise quantum R&D groups, algorithm developers, researchers and engineering teams that need to connect classical logic and constraints to quantum models and carry that ...

Quantum computing technology is complex, getting off the ground and maturing. There is promise of things to come. potentially changing the computing paradigm.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Overview  Quantum computing skills now influence hiring decisions across technology, finance, research, and national security sectors.Employers prefer cand ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning DOJ fails to indict in case of ...

Quantum computing is an emerging paradigm that leverages the principles of quantum mechanics to solve computational problems beyond the reach of classical computers. This article provides an overview ...

We introduce ANASTAARS, a noise-aware scalable classical optimizer for variational quantum algorithms such as the quantum approximate optimization algorithm (QAOA). ANASTAARS leverages adaptive random ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...

Introduction: This work presents an adaptive ant colony (AdCO) framework for dynamic task management in heterogeneous Non-Terrestrial Network–Internet of Things (NTN-IoT) systems integrating Unmanned ...