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 ...

Artificial intelligence (AI) has become integral to our daily lives, from virtual assistants like Siri to personalized recommendations on Netflix. As AI technology advances, quantum machine learning ...

The project aimed to develop a full stack of technologies to bring the practical advantages of quantum computing to industry in the near term Quantum computing is one of the frontiers of research and ...

Quantum technology is moving fast, and Infleqtion is right in the middle of it. They’re working on some big projects, like ...

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 ...

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 ...

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 ...

Motivation: Our goal is to establish a local infrastructure and a group of colleagues and graduate students focusing on research in the Quantum-NLP and ML domain. We aim at preparing and running ...

CML Unlocks AI’s Full Potential with Enhanced Pattern Recognition, Prediction, and Real-Time Decision-Making for Defense, Autonomous Systems, and Next-Gen Computing BOULDER, Colo.--(BUSINESS ...

In the quiet halls of the Duane Physics building at the University of Colorado Boulder, two JILA researchers, postdoctoral research associate Catie LeDesma and graduate student Kendall Mehling, ...