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 ...

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from ...

Quantum computing is entering a pivotal year as breakthroughs move from laboratory experiments to real business impact across ...

A partnership between Microsoft and Atom Computing has leveraged high-performance computing to successfully process 24 logical qubits, or quantum bits, marking a milestone in the quest to bring ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

A study has used the power of machine learning to overcome a key challenge affecting quantum devices. For the first time, the findings reveal a way to close the 'reality gap': the difference between ...

Quantum researchers from CSIRO, Australia's national science agency, have demonstrated the potential for quantum computing to ...

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 ...

Observing the flow of time at the quantum scale reveals a puzzling energy phenomenon: the energy required to simply read the time astronomically exceeds that consumed by the device's operation itself.

The past decade has seen significant advances and investment in quantum computing, and yet the devices we have today essentially have no practical purpose. That is down to two main reasons – the first ...