Companies evaluating AI want the most accurate machine learning models (ML) to predict or summarize business outcomes. However, many times achieving high levels of accuracy and confidence inflates expenses and erodes value versus adding to it. In this episode, Luther Birdzell and Scott King discuss what is and what is not AI, evaluating ML model accuracy against costs, and how to maximize your ROI when building or maintaining your models.

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