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 ...

New hybrid quantum applications show quantum computing’s ability to optimize materials science properties using Quantum-Enhanced Generative Adversarial Networks (QGANs) and fine-tune LLM models using ...

New hybrid quantum applications show quantum computing’s ability to optimize materials science properties using Quantum-Enhanced Generative Adversarial Networks (QGANs) and fine-tune LLM models using ...

Over the last 12 months it has been working with Sydney-based quantum chip specialist Silicon Quantum Computing (SQC), putting its machine learning processor – called Watermelon – through its paces.

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 ...

Understanding The FASQ Vision Defining Fault-Tolerant Application-Scale Quantum So, what exactly is this "FASQ" thing we keep ...

When a bond is unavailable for an asset manager to buy, perhaps due to liquidity constraints, the manager may search for a substitute bond with similar features. Methods exist to help the manager find ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...