Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

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 ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

At a time when data are doubling every two years, the U.S. is projected to create over 40 billion gigabytes of data by 2025. To prepare for the influx, Kennesaw State University associate professor ...

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 ...

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 ...

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 ...

D-Wave Quantum (NYSE:QBTS) develops quantum computing systems, hybrid solvers, and software platforms, driving technological ...

Quantum Science and Engineering is the study and application of the principles of quantum mechanics (such as superposition and entanglement) to develop new technologies that surpass the limits of ...

QTUM is a thematic ETF designed to provide exposure to companies involved in quantum computing and machine learning and uses a passive approach tied to the BlueStar Machine Learning and Quantum ...