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 ...

This collection supports and amplifies research related to SDG 9 - Industry, innovation and infrastructure. Quantum Machine Learning is currently listed as one of the most promising candidates for ...

Machine learning, and more generally, artificial intelligence, has achieved dramatic success over the past decade. This has been apparent in the tackling of notoriously challenging problems such as ...

Researchers from the RIKEN Center for Quantum Computing have used machine learning to perform error correction for quantum computers—a crucial step for making these ...

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 ...

A team of researchers has shown that even small-scale quantum computers can enhance machine learning performance, using a novel photonic quantum circuit. Their findings suggest that today s quantum ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

About a year and a half ago, quantum control startup Quantum Machines and Nvidia announced a deep partnership that would bring together Nvidia’s DGX Quantum computing platform and Quantum Machine’s ...