This new collaboration builds on an existing relationship that began earlier this year which saw IonQ’s quantum tech being used to improve the efficiency and cost-effectiveness of Hyundai’s electric vehicle (EV) batteries. The companies hope that the application of quantum machine learning to in-vehicle computer vision systems will allow both automated and human-controlled vehicles to better recognize objects on the road and beside it for safety and autonomous driving purposes. The duo claims they have already classified 43 different types of road signs for recognition using quantum machine learning tech. More: What is machine learning? Everything you need to know The next phase of the collaboration will focus on bringing the quantum-based computer vision improvements to Hyundai’s real-world test environment in an effort to simulate various practical driving scenarios. The companies seem to hope this phase will show how the application of quantum machine learning to computer vision systems can benefit both drivers and automated vehicles. Looking further forward, the pair expects to apply quantum processing to the task of helping Hyundai’s systems recognize a wider variety of 3D objects and potential hazards, including new road sign types, pedestrians, and cyclists. More: Quantum computers: Eight ways quantum computing is going to change the world Peter Chapman, president and CEO of IonQ, said that “from partnering on battery research for electric vehicles to image classification and object detection research for automated driving, we expect to see quantum computers become an even more integral part in developing novel transportation solutions.” IonQ plans to use its Aria quantum computer for this latest task, a system with 20 algorithmic qubits which it calls “the industry’s most powerful quantum computer based on standard application-oriented industry benchmarks.” More: IonQ teaming with US Department of Energy to produce domestic barium qubits for quantum computing
