A device made from superconducting qubits could prove a powerful technology for enabling practical quantum computing or more ...

Scientists in Australia have developed a quantum machine learning technique — a blend of artificial intelligence (AI) and quantum computing principles — that could change how microchips are made.

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 ...

What Makes Quantum Machine Learning Different QML isn’t just about running existing AI models on faster hardware. It’s about reimagining how learning itself happens.

In conclusion, tensor networks offer a breakthrough in addressing the efficiency-interpretability challenge in artificial intelligence, especially in quantum-inspired machine learning.

Vice President of AI & Quantum Computing, Paul Smith-Goodson gives his analysis of quantum machine learning models and IonQ's strategy to make it a reality.

Quantum machine learning (QML) combines quantum computing's power with ML's predictive capabilities to overcome classical algorithms' limitations.

By combining a new way of modeling quantum systems with increasingly sophisticated machine learning algorithms, researchers have established a method for classical machines to model and predict ...

According to Franco Nori, "Machine learning can play a pivotal role in addressing large-scale quantum computation and optimization challenges.

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 ...

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 ...