Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are designing an autonomous drone inspection solution that must run entirely at a remote construction site without reliable internet connectivity. The drone needs to generate concise natural-language summaries of detected safety risks on an embedded single-GPU device. Within Azure AI Foundry you must choose a model whose weights you can download and run locally while keeping GPU memory requirements low. Which model should you deploy?
Phi-2 is a 2.7-billion-parameter open-weight language model published by Microsoft. Because the weights can be downloaded from the Azure AI model catalog, the model can be executed completely offline and even on a single consumer-class GPU, making it suitable for edge scenarios that lack network connectivity. GPT-4 and GPT-3.5-Turbo are only available as hosted Azure OpenAI endpoints, so they require cloud access and cannot be run locally. DALL-E 3 is an image generation model, not a text-generation model, and also relies on a hosted service.
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Why is the Phi-2 language model suitable for offline use?
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What makes Phi-2 efficient for single-GPU devices?
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Microsoft Azure AI Engineer Associate AI-102
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