Hybrid Quantum: Classical Architectures For Machine Learning

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.

Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
EurekAlert!

New quantum encoding methods slash circuit complexity in machine learning

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 ...
Forbes

What Companies Look For When They Explore Quantum Machine Learning

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 ...
Morningstar

MicroCloud Hologram Inc. Releases Next-Generation Quantum Convolutional Neural Network Multi-Class Classification Technology, Driving Quantum Machine Learning Towards ...

SHENZHEN, China, Nov. 14, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has launched a groundbreaking technological ...