Advantages of using quantum computers for AIUseful when training high-dimensional data requires large computational resources Take advantage of nesting and entanglement
Quantum computing redefines the future of transportation management and optimization, fostering collaboration between the automotive and computing development industries
Volkswagen traffic management using quantum computing (urban traffic and travel route optimization)
Traffic congestion heat map in unoptimized (left) and optimized (right) flows
Calculate the optimal route in ms for each vehicle.
Traffic data collected by smartphones and in-vehicle transmitters is processed by non-quantum and quantum algorithms.
Ligand production acts as an inhibitor of target proteins
AI training with available ligand datasets → Ligand generation using trained models → Verification through in vitro experiments
Achieve quantum superiority using quantum machine learning models (QLSTM, QGAN)
Selected as the largest annual quantum algorithm project and received research support from the National Research Foundation of
Korea
The electrochemical CO2 reduction reaction (CO2 RR) reduces CO2 emissions and produces useful by-products.
Discovering promising CO2 RR catalysts has become a meaningful challenge, and machine learning is being applied to accelerate the rate of discovery.
This project aims to create new catalysts using generative quantum machine learning.
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