Quantum kernel learning for network service fault diagnosis | SoftBank case study | Q2B Tokyo 2024

Our friends at SoftBank and Keio University have made an exciting advance in quantum machine learning (QML) applied to telecom networks! These results combine novel advances in algorithm design and leverage the powerful combination of IBM utility-scale quantum computers augmented with our performance-management solution to enhance algorithmic performance. Learn more about this work in this presentation by Aravind Ratnam, Chief Strategy Officer at Q-CTRL, and Hiroshi Yamauchi Senior Manager, Research Institute of Advanced Technology, SoftBank Corp, at Q2B Tokyo 2024. Read the technical manuscript: https://arxiv.org/abs/2405.09724v1