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 ...

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 ...

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 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 ...

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 ...

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 ...

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from massive datasets and powering next-gen AI. That future might be closer than ...

Machine learning may sound relatively old-fashioned in the age of AI, but it remains a valuable and oft-used skill. Machine learning is the use of algorithms in computer systems to “learn” from data, ...