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

Quantum physics has a reputation for needing exotic hardware, from liquid-helium-cooled qubits to sprawling AI clusters, just ...

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 ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Machine learning can get a boost from quantum physics. On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in the ...

The vendor's system is capable of optimizing feature selection, which Alan Baratz says is the fundamental building block of machine learning. Feature selection is a key feature in quantum ...

Emily Fontaine is the global head of venture capital at IBM. The company’s venture fund, IBM Ventures, is a $500 million fund ...

In the context of quantum computing, open source platforms allow developers, researchers, and organisations to collaborate, ...

LOS ALAMOS, N.M., Feb. 22, 2022 — The field of machine learning on quantum computers got a boost from new research removing a potential roadblock to the practical implementation of quantum neural ...

There are high hopes that quantum computing's tremendous processing power will someday unleash exponential advances in artificial intelligence. AI systems thrive when the machine learning algorithms ...