Quantum researchers from CSIRO, Australia's national science agency, have demonstrated the potential for quantum computing to significantly improve how we solve complex problems involving large ...

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 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 ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

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 ...

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 ...

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 ...

However, while QBTS shares spiked in mid-March on news of the first of these advances, they have faltered since then. As of April 1, QBTS is actually down nearly 24% year-to-date (YTD). For many ...

Data is the new fuel. The potential for machine learning and deep learning practitioners to make a breakthrough and drive positive outcomes is unprecedented. But how to take advantage of the myriad of ...