Researchers have successfully demonstrated quantum speedup in kernel-based machine learning.

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 ...

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 ...

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 ...

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 ...

Quantum computing stocks surged last week after the U.S. Department of Commerce announced $2.013 billion in CHIPS and Science Act grants to nine quantum computing companies, marking one of the largest ...

Largest and longest-tenured pure-play quantum ETF holds direct exposure to IBM, D-Wave, Rigetti, and other companies named in ...

"Machine Learning in Quantum Sciences", outcome of a collaborative effort from world-leading experts, offers both an introduction to machine learning and deep neural networks, and an overview of their ...

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 ...

IonQ today laid out its five-year roadmap for trapped ion quantum computers. The company plans to deploy rack-mounted modular quantum computers small enough to be networked together in a datacenter by ...