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NEW QUESTION # 80
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: No
No, a summarization model is not used to transcribe spoken audio into written text; instead, an automatic speech recognition (ASR) or speech-to-text model performs the transcription, while a summarization model is used afterward to shorten the resulting text.
Box 2: No
No, a standard chat completion model cannot directly generate vector embeddings for semantic tasks. While both types of models process natural language, they are distinct architectures optimized for entirely different outputs:
Chat Completion Models (e.g., gpt-4o, Claude 3.5 Sonnet) are generative. They take a text prompt and predict the next sequence of words to produce a conversational text response.
Embedding Models (e.g., text-embedding-3-small) are extractive. They compress text into a fixed- length numerical array (a vector) that mathematically represents the underlying meaning, or semantic context, of that text.
Box 3: Yes
Yes, an embedding model can generate vector representations of the provided input. It turns text, words, or images into a list of numbers. These numbers capture the meaning of the data.
How Embeddings Work
An embedding model maps complex data into a simple numeric space.
Inputs: Words, sentences, whole documents, or images.
Outputs: A dense vector of floating-point numbers.
Meaning: Similar inputs get vectors that sit close to each other in that space.
Reference:
https://aimultiple.com/speech-recognition
https://www.debutinfotech.com/blog/understanding-the-role-of-embedding-in-models-like-chat-gpt
NEW QUESTION # 81
You deploy the Azure OpenAI service to generate images.
You need to ensure that the service provides the highest level of protection against harmful content.
What should you do?
Answer: A
NEW QUESTION # 82
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
To develop an application that analyzes text by using Azure Language in Foundry Tools, use the Azure Text Analytics client library package.
Azure Language text analysis workloads include capabilities such as sentiment analysis, key phrase extraction, named entity recognition, language detection, and other text analytics features. In application code, these text analysis capabilities are accessed by using the Azure Text Analytics client library .
The other options are incorrect:
Azure AI Projects client library is used for Foundry project and agent-related development.
Azure OpenAI client library is used to call Azure OpenAI model deployments.
Azure Speech SDK is used for speech recognition, speech synthesis, and other speech workloads.
NEW QUESTION # 83
You have a Microsoft Foundry project that contains a vision-enabled chat model deployment.
You are developing a Python application that sends a request containing a user prompt and a local JPEG image.
You need to include the image as binary data in the request.
To what should you set the image_url.ur1 field?
Answer: C
Explanation:
To pass a local JPEG image as binary data to a vision-enabled chat model deployment in a Microsoft Foundry project, you must set the url field inside the image_url object to a Base64- encoded Data URI string.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/gpt-with-vision
NEW QUESTION # 84
For each of the following statements, select if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement
Answer
Image analysis capabilities in Microsoft Foundry Tools can perform optical character recognition (OCR).
Yes
Image analysis capabilities in Microsoft Foundry Tools can generate captions and descriptive tags for images.
Yes
Image analysis capabilities in Microsoft Foundry Tools are designed primarily to create new images from text prompts.
No
Comprehensive and Detailed 150 to 250 words of Explanation From Azure AI Fundamentals/Course Guide
/topics:
The correct sequence is Yes, Yes, No.
The first statement is Yes. Azure Vision Image Analysis in Microsoft Foundry Tools supports optical character recognition (OCR). Microsoft documents Image Analysis 4.0 as supporting synchronous OCR through its Read capability, which extracts printed or handwritten text contained within images.
The second statement is also Yes. Image Analysis provides both captioning and image tagging. Captions generate a human-readable description of image content, while tags identify recognizable objects, scenes, actions, and other visual concepts. Microsoft explicitly lists capabilities such as Captions, Dense Captions, Tags, Object Detection, People detection, and Read/OCR as Image Analysis features.
The third statement is No. Image Analysis is primarily concerned with extracting information from existing images, not generating new images. Creating an image from a textual prompt is a generative AI/image- generation workload, typically performed by image-generation models. Image Analysis instead interprets visual input by extracting text, captions, tags, objects, and related information.
NEW QUESTION # 85
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