Modern AI systems have made it easy to tackle many problems previously thought out of reach of computers. These systems are so good that they have convinced even those working on developing them that they are sentient. However, despite the successes, many of these systems can be thought of as technological parrots. Parrots can mimic their owners, but do not have a true awareness of what they are saying, nor why they are saying it. Similarly, modern AI systems can mimic the patterns they have learnt from previous data, without having the true context of the problem which is being solved, nor understanding why a given prediction is returned.

Take about 30 seconds to stare at the above picture. Now close your eyes and try to recall the items you saw in the picture. How many were you able to recall? If you were able to recall all the items then you have a pretty good working memory. Our brains store information like this in the working memory and forgets it after sometime.

As someone who is interested in machine learning you know probably how hard it is to explain to a non digital native what it is what you exactly do. As a consultant with an interest in machine learning, I have found two sources that explain in very clear terms what machine learning is, how it basically works and in which way it can improve day-to-day business applications. Werner Vogels is the CTO from Amazon and in his TED-like speech called'Does AI make Apps Evil?' he clearly explains how machine learning is nothing more than simple technology that can be applied to build smarter applications. For example recommendation engines, fraud detection or marketing campaigns can absolutely benefit from it. Thomas Ball is an advanced analytics professional and writer at KDnuggets and he wrote an insightful article on predictive modelling titled'Data Science of Variable Selection: A Review'.