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 ...

Researchers from Tel Aviv University have developed a new method for simulating complex quantum systems that can be combined with cutting edge AI techniques The density of 6 fermions in a 2D harmonic ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

In their simulated system, image data is first simplified using a process called principal component analysis (PCA), which reduces the amount of information while preserving key features. A complex ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially 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 ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

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. When you purchase through ...

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 ...