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Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions

A global nonprofit organization is deploying a generative AI chatbot to provide educational content in multiple languages to underserved communities. They operate in regions with limited internet connectivity. The chatbot must work offline or with minimal data usage. The team has a moderate budget and limited technical staff. Which deployment strategy should they use?

⚠ Common exam trap

Candidates often confuse 'distillation on edge' with 'distillation on cloud VMs' (Option D), overlooking that edge deployment is the only way to guarantee offline functionality, while cloud VMs still require network access for inference.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Deploy a distilled version of the model on edge devices using TensorFlow Lite

Deploying a distilled version of the model on edge devices using TensorFlow Lite directly addresses the constraints of offline operation, minimal data usage, and limited technical staff. Distillation reduces model size and computational requirements, enabling inference on local hardware without cloud dependency, which is critical for underserved regions with intermittent connectivity.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Fine-tune an open-source model and host it on a cloud VM with auto-scaling

    Why it's wrong here

    Requires internet and may not be optimized for low-connectivity areas.

  • Deploy a distilled version of the model on edge devices using TensorFlow Lite

    Why this is correct

    Enables offline inference with low resource usage.

  • Host a large foundation model on Google Cloud and use a mobile app to send API requests

    Why it's wrong here

    Requires constant internet connectivity.

  • Deploy a distill of a smaller model on Google Cloud VM instances

    Why it's wrong here

    Still requires connectivity and may be costly.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.