Producing new data similar to the training data - This is the correct answer. Generative AI models are designed to generate new data that is similar to the training data, such as creating new images, text, or music. They learn patterns from the input data and use this knowledge to produce new, original content.
Classifying data into predefined categories - This is a characteristic of classification models, not generative AI. Classification models categorize data into specific labels or classes, but they do not generate new data.
Detecting anomalies in data patterns - Anomaly detection is typically done by models designed for identifying outliers or unusual patterns in data, not generative AI models.
**Compressing data into lower-dimensional representations **- This is the purpose of dimensionality reduction techniques (e.g., PCA), which aim to reduce the number of features in data while preserving important information. It is not related to generative AI.
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Microsoft Azure AI Fundamentals AI-900
Describe features of generative AI workloads on Azure
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