The Quantum Shift in Machine Learning

Esma Aı̈meur, Gilles Brassard A, Sébastien Gambs

Latika Kharb, Deepak Chahal

In the realm of artificial intelligence (AI), the integration of quantum computing with machine learning (ML) has sparked a significant shift in how we approach problems that were once deemed computationally infeasible. Quantum Machine Learning (QML) represents an exciting intersection of quantum mechanics and machine learning, potentially revolutionizing areas such as optimization, pattern recognition, and data analysis. Although quantum computing itself is still in its infancy, the synergy between quantum theory and classical machine learning algorithms promises to unlock new capabilities that classical computing could never achieve. This paper delves into the latest advancements in Quantum Machine Learning, its theoretical underpinnings, practical applications, and the challenges that researchers face as they explore this rapidly growing field.

Tarun Kumar Vashishth, Vikas Sharma, Kewal Krishan Sharma +1 more

Quantum machine learning (QML) is an emerging interdisciplinary field that combines the principles of quantum mechanics with machine learning algorithms, offering promising solutions to complex computational problems. This paper provides an extensive introduction to quantum machine learning, exploring the synergies between artificial intelligence and quantum technology. It begins by elucidating the foundational concepts of quantum computing, including quantum bits (qubits), quantum gates, superposition, and entanglement. Subsequently, the paper delves into the basic principles of machine learning and the challenges faced by classical methods in handling large-scale data and solving computationally intensive tasks. With a strong foundation in place, the focus shifts towards the integration of quantum mechanics with machine learning, showcasing the advantages and potential breakthroughs QML offers over classical approaches. The exploration of quantum algorithms for machine learning, such as quantum support vector machines (QSVM), quantum neural networks (QNN), and quantum variational algorithms, reveals the power of quantum-enhanced techniques in data classification, regression, and clustering.

Charles R. Giardina

Shivani Saini, P.K. Khosla, M. Kaur +1 more

Agnieszka Gryz

Superpowers such as the US, China and the United Kingdom have recognised quantum and Artificial Intelligence/ Machine Learning (AI/ML) based technologies as strategically important from geopolitical, social and economic perspectives. Those technologies have the potential to shift geopolitical points of gravity and either strengthen or weaken them. This article reviews the United Kingdom's strategic approach to quantum and AI/ML technologies and how those technologies could affect the UK’s geopolitical position.