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As we make product that are Artificial Intelligence (AI) enabled, there are no methods to mark its competency levels. Though we find co-relation in competency levels of man and machines there are no ways this can be judged. This paper tries to explain the competency levels of humanโs and finally create a table for the AI competency levels, that can be applied to systems in general.From human perspective I try to explain about knowledge gathering, pattern recognition, finding solutions, generalizing patterns and co-relations between patterns as the basis for identifying human competency.With experience we tend to solve many problems with ease from the gathered knowledge. This is where you use methods without consciously knowing that you are following certain process you developed, or you think is the best way.There is a pattern for every system in nature. This is true in your life, man-made gadgets, the nature around or anything you come across. Some patterns are common, some are co-related, some are comparative, with which we can derive solutions.Whatever method we follow, we always want to solve issue within a short period of time. Time is of essence that determines the efficiency. Efficiency can make a difference in certain critical solutions.From all these competency aspects there is a parallel we can draw with AI enabled hardware. This can be summarized as a competency chart to measure the maturity levels of artificial Intelligence.
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