The biological systems of the brain were fine for their ability to function reliably and effectively in high-noise environments. Biological pathways were built from brain components of highly adaptive or flexible interactions that could be low-precision, unpredictable, or extremely simultaneous. The capacity of brain networks to organize themselves and their pattern structure are two of the most intriguing features. Current findings in the addition of Neural Networks (NN) have revealed some intriguing ideas on Artificial Neural networks (ANN) and Convolutional Neural networks (CNN). Only largescale advanced neural simulations could be built, making it possible to understand these ideas and apply them to real problems. Large-scale network simulators are achievable with the latest enhancements to low-cost multiprocessor systems. Conceptual paradigms of NN methods for designing, generating, and evaluating advanced neural systems were discussed in this study.