1. The article discusses the use of neural networks in enhancing randomized testing by focusing on novelty-based test selection to improve functional coverage. 2. It highlights a study where different neural network methods were applied to guide the selection of configuration register values in an automotive RADAR signal processing unit, significantly reducing the number of simulations needed. 3. The results show that using a coverage-focused neural network can achieve a substantial reduction in the simulations required to reach high coverage levels, though with variability.