IonQ Hyundai quantum computing for object detection

IonQ e Hyundai, partnership per utilizzare il Quantum Computing per il rilevamento di oggetti thumbnail

IonQa company active in quantum computing, e Hyundai Motor Company have announced an expansion of their partnership with a new project. The two companies plan to apply quantum machine learning to image classification and 3D object detection for future mobility.

These two characteristics are among the most critical problems facing automakers on their journey to self-driving vehicle production. Together, IonQ and Hyundai will seek to improve computational functionality through more efficient machine learning using quantum computers. Thanks to these, in fact, it will be possible to process huge amounts of data faster and with greater precision than traditional systems.

Using image encoding in quantum states, IonQ is already classifying 43 kinds of road signs using its own quantum processors. In the next phase, the two companies will apply IonQ’s machine learning data to Hyundai’s test environment. In fact, the two companies will later simulate various real-world scenarios.

IonQ and Hyundai, from road signs to pedestrian and cyclist detection

As part of this project IonQ and Hyundai will seek to develop quantum techniques for 3D object detection. The goal is therefore to move from road signs to other “objects” such as pedestrians or cyclists.

Performing object recognition activities on IonQ’s latest quantum computer called “Aria”. This supercomputer will enable more efficient processing at lower costs, leading to the development of safer and smarter mobility in the future. With 20 algorithmic qubits (#AQ), IonQ Aria is the industry’s most powerful quantum computer based on standard application-oriented benchmarks.

The news also marks the latest initiative undertaken by IonQ and Hyundai Motor, after the January announcement. The announced partnership saw quantum computers committed to improving the performance, cost and safety of lithium batteries used in electric vehicles.