The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

Researchers at North Carolina State University have unveiled Rainbow, a first-of-its-kind multi-robot self-driving laboratory that autonomously discovers high-performance quantum dots—semiconductor ...

This collection supports and amplifies research related to SDG 9 - Industry, innovation and infrastructure. Quantum Machine Learning is currently listed as one of the most promising candidates for ...

The quantum computing trade has shifted from a speculative bet to an identifiable, investable theme, and the three exchange-traded funds that best capture it each take a different angle on the same ...

A team of researchers has shown that even small-scale quantum computers can enhance machine learning performance, using a novel photonic quantum circuit. Their findings suggest that today s quantum ...

Quantum computers are inching closer to practical deployment, but shielding fragile quantum information from errors is still very challenging. Now, a machine-learning-based decoder offers a strategy ...

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 ...

The rise of the humanoid robotic machines is nearing. Robotics is now revolutionizing numerous industry sectors through the integration of artificial intelligence, machine learning and reinforcement ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...