"Machine Learning in Quantum Sciences", outcome of a collaborative effort from world-leading experts, offers both an introduction to machine learning and deep neural networks, and an overview of their ...

Artificial intelligence (AI) and quantum technologies represent two of the most transformative scientific frontiers of the 21st century. While quantum ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

For years, progress in artificial intelligence has followed a simple rule: make it bigger ...

New hybrid quantum applications show quantum computing’s ability to optimize materials science properties using Quantum-Enhanced Generative Adversarial Networks (QGANs) and fine-tune LLM models using ...

Quantum machine learning is being explored as the next frontier in cybersecurity, but new research shows it remains far from replacing established artificial intelligence systems in detecting phishing ...

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...

Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a ...

Quantum computing made significant strides in 2024, but it’s yet to demonstrate a practical advantage over classical digital computers, according to a recent trends report released by Forrester ...