Artificial Intelligence (AI) two words, two separate meanings: Artificial means ‘made by people’ and Intelligence means ‘the ability to learn, understand and make judgments or have opinions that are based on reason’.
Each AI domain has its own use case. For example, a reinforcement learning model would not be the preferred choice to perform a standard computer vision task such as defects in medical imagery. In this case, the preferred paradigm is of supervised learning.
Genetic Algorithms are adaptive heuristic search algorithms that are inspired by Charles Darwin’s theory of natural selection to solve optimisation problems. They are robust, provide optimisation over large space states and unlike traditional AI, do not break on slight change in input or presence of noise.
Validating an AI is subject to the purpose of the AI, and the success rate should be clearly defined prior testing. If an NLP AI has only been trained on financial customer care data from existing customers, and the test questions are all about financial forecasting then the AI would in most cases failed the test.