One possible solution is quantum machine learning (QML). QML introduces a fundamentally different approach to learning and optimization by applying quantum principles to AI algorithm design.

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing.

Finbold’s AI price prediction tool relied on three machine learning models to figure out where the Bitcoin price might be by August 1, 2025.

XRP is entering one of its most closely watched trading windows in recent months, with the looming release of 1 billion XRP tokens by Ripple.

The Quantum Machine Learning (QML) Playground is an interactive web application designed to visualize the inner workings of quantum machine learning models in an intuitive and educational manner.

At the forefront of discovery, where cutting-edge scientific questions are tackled, we often don't have much data. Conversely, successful machine learning (ML) tends to rely on large, high-quality ...

This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning to solve ...

QML implements quantum algorithms to solve machine learning problems. The process requires quantum circuits to perform data encoding, followed by transformation steps and pattern extraction.

A current approach uses classical machine learning (CML) algorithms, but they require large datasets, and their performance degrades in small-sample, nonlinear settings. The Australian researchers, ...

In a first, Australian scientists turned to quantum machine learning to model semiconductor design, outperforming classical approaches.

Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new developments for machine learning algorithms.