Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are designing an Azure solution for a retail call centre. Incoming customer calls must be converted to text in near real time and immediately summarized so that agents see a concise recap of each interaction. Your goal is to minimize custom model training and infrastructure management by relying on fully managed Azure AI offerings. Which Azure AI Foundry service combination should you recommend?
Use Azure AI Document Intelligence with the prebuilt receipt model and Azure Cognitive Search with semantic ranking.
Use Azure AI Vision with a custom model for transcription and Azure Machine Learning with a fine-tuned GPT-2 model for summarization.
Use Language Understanding (LUIS) to transcribe audio and Custom Voice to generate summaries.
Use Azure AI Speech for real-time transcription and Azure OpenAI Service for text summarization.
Azure AI Speech provides fully managed, real-time speech-to-text capabilities that can continuously transcribe live audio streams without the need to train custom acoustic models. Azure OpenAI Service exposes hosted large language models (such as GPT-3.5 Turbo) that can perform text summarization through simple prompt engineering, again with no custom training or infrastructure management. The other options either use services that do not support the required modality (Vision, Document Intelligence, LUIS, Custom Voice) or require building and hosting custom models in Azure Machine Learning, which violates the requirement to rely on pre-built managed offerings.
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Microsoft Azure AI Engineer Associate AI-102
Plan and manage an Azure AI solution
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