Informa Connect: Quantum machine learning with near-term quantum computing

Our Head of Machine Learning, William Clements, wrote an article for Informa Connect discussing the progress of near-term quantum computers and the work ORCA Computing is doing to investigate applications for generative modelling, with implications for finance.

William talks about how modern generative models such as generative adversarial networks (GANs) or diffusion models rely on learning transformations between data and a high-dimensional “latent space”.

He goes on to explain how we find using a quantum latent space, produced with existing photonic quantum computers, can lead to improved performance on some tasks. In fact, to our knowledge, we performed the first demonstration of a generative modelling task using a quantum device in the “quantum advantage” regime that is too large to simulate even by a supercomputer.

Overall, our work demonstrates that generative models that use quantum latent spaces exhibit different statistical properties than those that use classical latent spaces. Our approach can also be scaled to large-scale data and quantum processors in the quantum advantage regime, achieving better performance than commonly used distributions.

Read the Informa Connect article