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As we all know, through the judicial examination, you need to become a lawyer, when the teacher is need through the teachers' qualification examinations. If you want to be an excellent elites in this line, you need to get the Microsoft Azure AI Fundamentals certification, thus it can be seen through the importance of qualification examination. Only through qualification examination, has obtained the corresponding qualification certificate, we will be able to engage in related work, so the AI-901 Test Torrent is to help people in a relatively short period of time a great important tool to pass the qualification test.
NEW QUESTION # 65
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 66
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each connect selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: Using Azure Speech in Foundry Tools for batch transcription requires live audio input from a microphone. = No Batch transcription is used to process stored audio files, not live microphone input. Live microphone input is used for real-time speech recognition scenarios.
Statement 2: Azure Speech in Foundry Tools can analyze video frames to detect and label objects while transcribing audio. = No Azure Speech is for speech capabilities such as speech recognition, speech synthesis, and speech translation.
Detecting and labeling objects in video frames is a computer vision/video analysis capability, not an Azure Speech capability.
Statement 3: Speech translation in Azure Speech in Foundry Tools can translate spoken audio into text in another language. = Yes Speech translation converts spoken input in one language into translated text in another language.
NEW QUESTION # 67
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The correct answer is API endpoint . After a generative AI model is deployed in Microsoft Foundry, the deployment exposes an inference endpoint through which external applications can submit requests and receive generated responses. Microsoft Foundry documentation describes deployed models as being accessible programmatically through an endpoint and associated credentials. Applications invoke the relevant REST API or SDK against this endpoint and specify the deployed model as required by the API.
An embedding vector is a numerical representation of semantic information used for similarity search, retrieval, and grounding; it is not the network interface through which a deployed model is invoked. A training dataset contains data used to train or fine-tune a model and is not called when performing inference.
A URL parameter can be part of an API request, but it does not represent the deployed model ' s callable interface.
This directly aligns with the AI-901 objective to deploy a model and interact with it in the Foundry portal and to create lightweight applications that invoke deployed generative AI models through supported APIs and SDKs.
NEW QUESTION # 68
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 69
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to develop an application that sends a message containing text and an image URL.
The solution must ensure the quickest response time.
Which message structure should you include in the request?
Answer: C
Explanation:
To achieve the fastest possible response time in Microsoft Foundry/Azure AI, you must combine the text prompt and image URL into a single user message, utilizing a system message for instructions, and opting for a low-latency model like gpt-4o-mini.
Sending separate requests or splitting the text and image into different messages increases network overhead and conversation context length, both of which add unnecessary latency.
Note:
1. Required Message Structure
You should include both a system message and a custom user message in your API request payload:
System Message: Use this to define the context, guardrails, and explicit format requirements. It sets up the model behavior before the image is even processed, optimizing processing efficiency.
User Message (Custom Message): This is where you pass your text prompt and the actual image reference.
2. Request Handling: Single vs. Separate Requests
You must send the text item and the image item in the same single request.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/transitioning-from-azure-language-features-to-foundry-models/4524092
NEW QUESTION # 70
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