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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q46-Q51):

NEW QUESTION # 46
An organization wants to use generative AI to create a chatbot that can answer customer questions about their account balances. They need to ensure that the chatbot can access previous portions of the conversation with the customer. Which prompting technique should they use?

A. Use zero-shot prompting.
B. Use few-shot prompting.
C. Use prompt chaining.
D. Use role prompting.

Answer: C

Explanation:
Prompt chaining (or conversational memory/context management) is the technique used to maintain the conversational context. It involves feeding previous turns of a conversation (or a summary of them) back into the model along with the current user query, allowing the chatbot to "remember" and reference past interactions for coherent and contextually relevant responses, especially crucial for tasks like checking account balances that span multiple turns.
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NEW QUESTION # 47
A software developer needs a highly efficient, open-source large language model that can be fine-tuned on a local machine for rapid prototyping of a chatbot application. They require a model that offers strong performance in natural language understanding and generation, while being lightweight enough to run on limited hardware. Which Google-developed family of models should they use?

A. Gemma
B. Imagen
C. Veo
D. Gemini

Answer: A

Explanation:
Gemma is Google's family of lightweight, state-of-the-art open models, built from the same research and technology used to create the Gemini3 models. They are designed for developers to build innovative AI applications on their local machines or in the cloud, offering a balance of performance and efficiency suitable for limited hardware and rapid prototyping. Veo is for video generation, Gemini is typically larger and more general-purpose, and Imagen is for image generation.
________________________________________

NEW QUESTION # 48
A highly regulated financial institution wants to use Gemini as the core decision engine for a loan approval system that will deterministically approve or reject loan applications based on a strict set of predefined criteria. Why is this an inappropriate use case for Gemini?

A. Gemini deployment for this scenario would be too expensive and complex.
B. Gemini cannot integrate with required financial databases.
C. Gemini is not equipped to handle structured numerical data for financial assessments.
D. Gemini is designed for flexible content generation and inference, not rigid rule-based decisions.

Answer: D

Explanation:
Gemini, as a large language model, excels at flexible content generation, summarization, understanding, and inference. However, it is not designed for deterministic, rule-based decision-making that requires absolute consistency and adherence to strict, predefined criteria, as is common in highly regulated financial systems like loan approvals. Such systems typically require traditional programming logic or specific rule engines for auditable and consistent outcomes.
________________________________________

NEW QUESTION # 49
A company is developing a conversational AI chatbot. They need to ensure the chatbot can engage in human- like conversations and provide accurate information. What should they do to enhance thechatbot's ability to understand and respond effectively to user prompts?

A. Use prompt engineering techniques, like few-shot prompting, to provide the chatbot with examples of successful interactions.
B. Limit the chatbot's training data to prevent it from learning irrelevant information.
C. Lower model temperature setting to produce more consistent and predictable responses.
D. Use strict keyword matching to ensure that the chatbot only responds to specific commands.

Answer: A

Explanation:
Prompt engineering, especially techniques like few-shot prompting (providing examples of desired input- output pairs), is crucial for guiding a generative AI model to understand context and generate relevant, human- like responses. Limiting data or using strict keyword matching would severely restrict the chatbot's conversational ability, and lowering temperature makes responses less creative, not necessarily more understanding.
________________________________________

NEW QUESTION # 50
An organization wants to use generative AI to create a marketing campaign. They need to ensure that the AI model generates text that is appropriate for the target audience. What should the organization do?

A. Use few-shot prompting.
B. Adjust the temperature parameter.
C. Use role prompting.
D. Use prompt chaining.

Answer: C

Explanation:
Role prompting is a technique where you instruct the generative AI model to "act as" a specific persona or character. By assigning the model a role (e.g., "Act as a marketing expert writing for a young, tech-savvy audience"), you can guide its tone, style, and content to be appropriate for the target audience of the marketing campaign.
________________________________________

NEW QUESTION # 51
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2025 Test Generative-AI-Leader Guide | Professional Generative-AI-Leader: Google Cloud Certified - Generative AI Leader Exam 100% Pass

Quiz 2025 Generative-AI-Leader: Latest Test Google Cloud Certified - Generative AI Leader Exam Guide

Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q46-Q51):

Generative-AI-Leader exam dumps, prep4sure Generative-AI-Leader real test, Google Generative-AI-Leader prep

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