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Holdout forecasts are a critical tool in AI forecasting, providing a robust method for validating the accuracy of predictive models. This technique involves dividing your data into two sets: one for training the AI and the other for testing its predictions. This approach helps ensure that your model can effectively perform with new, unseen data, simulating real-world conditions as closely as possible.