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 ...

Pushing against years of scepticism, an analysis suggests quantum computers may offer real advantages for running machine ...

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 ...

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 ...

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 ...

As proposed and demonstrated by the Los Alamos team, the architectures and techniques proposed to mitigate or altogether ...

We are looking for a Doctoral Researcher for Quantum-inspired tensor network machine learning solvers for super-moiré van der Waals materials.

Lawrence Livermore National Laboratory (LLNL) has been selected to lead a project that will receive $4.1 million in funding ...

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 ...

For centuries, scientists have been on a thrilling quest to understand the universe's building blocks. At CERN, the European Organization for Nuclear Research, the Large Hadron Collider (LHC) smashes ...

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 ...