The Pitfalls of Using AI as the Input of Another AI

In the previous article, I briefly mentioned how using AI sequentially is a nightmare. Whenever an AI is used as input for another, the individual errors of each model quickly add up to unacceptable levels or, simply put, catastrophic failure. Moreover, as you add more nodes to the chain, the problem gets exponentially worse. In this article, I expand on the matter, explaining the intuition to why sequential models fail and how we can remedy some of these issues. The following discussion is of paramount interest to anyone developing complex AI pipelines, such as using object detection to find objects of interest and applying some other model to these objects.