Artificial intelligence algorithms and models are two concepts that are often confused. Simply put, an artificial intelligence model is a program that exhibits intelligent behavior, while an algorithm is a set of explicit steps that create this program. These two should not be confused. As an analogy, if we compare it to cooking, the algorithm is the recipe, and the model is the prepared dish.
The subject of artificial intelligence research is algorithms. Like other sciences, artificial intelligence aims for determinism. Therefore, AI scientists need to know how to generate artificial intelligence models explicitly and systematically, and this step (the algorithm) must be universal, meaning it should be effective in most situations, and even if it is ineffective, the reasons must be understood.
Machine learning has blurred the distinction between algorithms and models. Since machine learning models continuously learn, they are never in a final finished state. As a result, machine learning algorithms are also constantly operating.
