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2. Discovery is the ability of an intelligent system to learn from data without upfront human intervention. Often, this needs to be done without being presented with an explicit target. It relies on t…

3. Once the data set is understood through intelligent discovery, supervised approaches are applied to predict what will happen in the future. These types of problems include classification, regressio…

4. Applications need to support interaction with humans in a way which makes outcomes recognizable and believable. For example, when one builds a predictive model, it is important to have an explanat…

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   AI without UX is of limited utility. UX is what distributes that intelligence across the organization and pushes it to the edge – where it can be consumed by practitioners and subject matter exper…

6. Intelligent systems are designed to detect and react as the data evolves. An intelligent system is one that is always learning, lives in the workflow and is constantly improving. In the modern dat…