JAKARTA - In the future, Hyundai will have technology that can more accurately recognize objects for its autonomous cars, this breakthrough aims to provide driver safety.
Therefore, IonQ, the owner of the technology, announced that it is expanding its relationship with Hyundai to apply quantum computing-based technology to autonomous cars to make it easier to recognize objects in the real world.
In fact, the two had collaborated earlier this year, in which quantum IonQ technology was used to improve the efficiency and cost-effectiveness of Hyundai's electric vehicle (EV) batteries.
IonQ hopes that applying quantum machine learning to in-vehicle computer vision systems will enable automated and human-controlled vehicles to better recognize objects on the road, as well as safety and autonomous driving.
"From partnering in battery research for electric vehicles to image classification and object detection research for automated driving, we look forward to seeing quantum computers become a more integral part of developing new transportation solutions," said IonQ president and CEO Peter Chapman. , Thursday, April 21.
According to Chapman, IonQ plans to use the Aria quantum computer for this latest task, a 20 qubit algorithmic system that he calls the industry's most powerful quantum computer based on standard application-oriented industry benchmarks.
The two companies claim that they have classified 43 different types of road signs for recognition using quantum machine learning technology.
The next phase of the collaboration will focus on bringing quantum-based computer vision enhancements to Hyundai's real-world test environment, in an effort to simulate various practical driving scenarios.
Apparently, the company hopes this phase will demonstrate how applying quantum machine learning to computer vision systems can benefit drivers and automated vehicles.
In addition, the two will also apply quantum processing to the task of helping Hyundai's systems recognize more 3D objects and potential hazards, including new types of road signs, pedestrians and cyclists going forward.
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