How AI Is Finding Patterns And Anomalies In Your Data

One of the most widely adopted of the seven patterns of AI is the Patterns and Anomalies pattern. Machine learning is particularly good at digesting large amounts of data very quickly and identifying patterns or finding anomalies or outliers in that data. The "pattern-matching pattern" is one of those applications of AI that itself seems to repeat often, and for good reason as it has broad applicability. The goal of the Patterns and Anomalies pattern of AI is to use machine learning and other cognitive approaches to learn patterns in the data and discover higher order connections between that data. The objective is to determine whether a given data point fits an existing pattern or if it is an outlier or anomaly, and as a result find what fits with existing data and what doesn't.