Towards creating AI with instincts

In late August 2019, researchers at Google released a paper titled Weight Agnostic Neural Networks, opening our eyes to a missing piece of the puzzle in our quest to create Artificial Intelligence (AI) as close as possible to natural brains: instinct. This article covers the ways of finding Artificial Neural Network (ANN) architectures until now, points out the importance of instinct in a brain and, for the detail-hungry, describes how instinct can be incorporated into AI. The architecture of an ANN, in a nutshell, refers to the number, arrangement and connections of neurons therein. When building an ANN to solve a problem, the best architecture possible under all constraints is desired. After all, it does not pay to have a sub-optimal solution.