Databricks Generative AI Engineer Associate exam dumps

Databricks Generative AI Engineer Associate practice question 152 of 306

Databricks Certified Generative AI Engineer Associate. Free level, Databricks. Free question with the correct answer and a full explanation.

Databricks Generative AI Engineer Associate Question 152

Single answer

You are designing a customer support chatbot for a retail company. The chatbot must handle a wide variety of questions about products, orders, and returns. It needs to provide accurate, context-aware responses, support multiple languages, and prioritize cost-efficiency. Which LLM would be the best choice for this application?

  1. A

    An open-source LLM fine-tuned on customer support datasets

  2. B

    A general-purpose LLM hosted and maintained by a cloud provider with multilingual support

  3. C

    A task-specific LLM pre-trained for e-commerce applications

  4. D

    A lightweight LLM optimized for low-latency inference but with limited multilingual capabilities

Show answer and explanation

Correct answer: B

Explanation

For a customer support chatbot with requirements for multilingual support, accuracy, and cost-efficiency, a general-purpose LLM hosted by a cloud provider is the best choice. It provides the necessary capabilities out-of-the-box, including multilingual support and scalability, while reducing operational costs and complexity compared to fine-tuning or hosting models independently.

  • A. Incorrect.

    While an open-source LLM fine-tuned on customer support datasets can provide some customization, it might require significant engineering effort for multilingual support and may not be cost-effective in terms of infrastructure requirements.

  • B. Correct.

    A general-purpose LLM hosted and maintained by a cloud provider with multilingual support would meet the requirements for accuracy, context-awareness, multilingual capabilities, and cost-efficiency, as it eliminates the need for extensive infrastructure and maintenance.

  • C. Incorrect.

    A task-specific LLM pre-trained for e-commerce applications might be useful for domain-specific nuances but may not adequately handle multilingual support or general customer queries beyond e-commerce contexts.

  • D. Incorrect.

    A lightweight LLM optimized for low-latency inference would be cost-efficient but likely fails to meet the accuracy and multilingual requirements for the chatbot.

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