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A groundbreaking deep learning model, developed by researchers from KTH Royal Institute of Technology, is revolutionizing the field of aerodynamics by accurately predicting airflow dynamics while minimizing computational expenses. This model utilizes neural network architecture and a reduced order model approach to streamline the engineering design process.