In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dig deeper into the Patterns & Anomalies pattern of AI. The primary objective of this pattern is to find which one of the things is like the other and which is not. Example use cases include fraud detection and risk analysis, discovering patterns among data and surfacing insights, automatic error detection or correction, intelligent monitoring, finding hidden groups of data, finding best matches to given data, predictive text, and similar applications. Join us as we dig deeper into this pattern.
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