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 ...

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

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 ...

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 ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...