Determine the Differences Between Predictive AI and Generative AI CERTIFIED-AI-EXPERT Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   How do the data requirements of predictive AI typically differ from those of generative AI?

   • ABoth require equally large labeled datasets
   • BPredictive AI requires large unlabeled datasets, while generative AI requires labeled historical data
   • CPredictive AI requires labeled historical data, while generative AI can often use large unlabeled datasets
   • DBoth require small, curated datasets with no labels
   Reveal Solution Discussion Select an answer first
2. 2application · medium

   A retail company wants to reduce stockouts by anticipating which products will run low in the next two weeks. They have five years of historical sales data with timestamps and product IDs. Which approach best fits this requirement?

   • AUse a generative model to synthesize new sales records for the next two weeks.
   • BUse a time-series forecasting model to predict future demand for each product.
   • CUse a regression model to predict the exact date each product will run out.
   • DUse a classification model to label each product as 'in stock' or 'out of stock' for the next two weeks.
   Reveal Solution Discussion Select an answer first
4. 3application · medium

   A startup must choose between building a model to predict equipment failures and one to generate realistic images for a design tool. They have limited GPU resources. Which consideration is most relevant to their choice?

   • ABoth model types have identical computational and data requirements.
   • BGenerative models require labeled data, while predictive models can use unlabeled data.
   • CGenerative models often require more computational resources and larger datasets than typical predictive models.
   • DPredictive models always require more computational resources than generative models.
   Reveal Solution Discussion Select an answer first
5. 4application · medium

   A manufacturing company wants to use AI to (1) predict when a machine will fail and (2) generate synthetic training images of defective parts. Which pair of outputs best matches these two tasks?

   • AA new image of a defective part; a failure probability score for the machine.
   • BA time-series forecast of failures; a time-series forecast of image quality.
   • CA failure probability score for the machine; new images of defective parts.
   • DA classification label for the machine; a classification label for the images.
   Reveal Solution Discussion Select an answer first
6. 5foundation · easy

   Which of the following is a common technique used in predictive AI?

   • ARegression
   • BTransformer-based language models
   • CVariational Autoencoders (VAEs)
   • DGenerative Adversarial Networks (GANs)
   Reveal Solution Discussion Select an answer first