Real world is full of variables and dynamics, where advanced systems bring human and artificial intelligence (AI) together. This is to leverage their complete abilities which complement each other and excel in their own space. AI is very efficient where we have a well-defined and controlled environment, whereas humans are better in general.
Machine learning algorithms perform effectively at finding complex and subtle patterns in huge data sets. But the human brain can process information efficiently even with small data sets, when there is noise and uncertainty in the input – or dynamic data.
This is why companies are giving more focus on hybrid models, where they take advantage of both human and AI.
As AI depends on enormous training data, human moderators are required to work on historical data to format them into features and labels. So that, it can be used as input for training the system efficiently. In addition to this, to keep a check on the performance of the system and to help it learn continuously, advanced hybrid models continuously validate by random sampling of data manually and training the system with an updated dataset prepared manually.
AI is here to stay, as this general-purpose technology can be integrated with nearly every industry. With more advanced and complex models, it’s growing stronger and stronger every day. More complex models require more input data and sampling by humans, to guarantee its accuracy. Hybrid-models are the future considering the real life dynamics and advancement of AI.