Volkswagen Refining Machine Learning on D-Wave System

Researchers at Volkswagen have been at the cutting edge of implementing D-Wave quantum computers for a number of complex optimization problems, including traffic flow optimization, among other potential use cases. These efforts are generally focused on developing algorithms suitable for the company's recently purchased 2000-qubit quantum system and have expanded to a range of new machine learning possibilities, including what a research team at the company's U.S. R&D office and the Volkswagen Data:Lab in Munich are calling quantum-assisted cluster analysis. The art and science of clustering is well known for machine learning on classical computing architectures, but the VW approach that has been tailored to perform well on a quantum processor has undergone major alterations. As the team describes, to be mapped to the D-Wave architectures, the problem has to be expressed as a quadratic unconstrained binary optimization problem. Once done, the accuracy of results is similar to the what a classical clustering algorithm can produce.