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 ...

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 ...

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 ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language translation. A quantum counterpart—known as a quantum convolutional neural ...

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 ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

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 ...

Introduction: The Portfolio Optimization Process Needs to Be Revamped. For decades, portfolio optimization has been the pinnacle of modern finance. In the 1950s, with the introduction of Harry ...

BEIJING, Sept. 17, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, announced that they ...

Classical computations rely on binary bits, which can be in either of the two states, 0 or 1. In contrast, quantum computing is based on qubits, which can be 0, 1, or a superposition or entanglement ...

Andrew Jenkins has worked as an information analyst for an intelligence agency in Washington, D.C., for over 14 years. He is the author of the 2022 book, The Devil Made Crypto. Follow him on LinkedIn.