Drag and Drop Question Match the types of AI workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each…

The correct answer is Knowledge mining; Computer vision; Natural language processing. The three correct workload types map to their scenarios as follows: Knowledge mining involves extracting insights and information from large volumes of unstructured data (e.g., documents, PDFs); Computer vision handles tasks involving image or video analysis such as object…

Submitted by parkjh· Mar 30, 2026Identify features of common AI workloads - this aligns with the Microsoft Azure AI Fundamentals (AI-900) exam objective: 'Describe common AI workload features' under the domain of 'Describe Artificial Intelligence workloads and considerations.'

Question

Drag and Drop Question Match the types of AI workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point. Answer:

Exhibit

Answer Area

Drag items

Anomaly detectionComputer visionKnowledge miningNatural language processing

Correct arrangement

Knowledge mining
Computer vision
Natural language processing

Explanation

The three correct workload types map to their scenarios as follows: Knowledge mining involves extracting insights and information from large volumes of unstructured data (e.g., documents, PDFs); Computer vision handles tasks involving image or video analysis such as object detection, image classification, or facial recognition; and Natural language processing (NLP) deals with understanding, interpreting, and generating human language in text or speech form. Each of these AI workload types has a distinct domain that aligns with specific real-world scenarios involving data type and the nature of the task.

Topics

#AI Workload Types#Computer Vision#Natural Language Processing#Knowledge Mining

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