FREE PDF 2025 GOOGLE UNPARALLELED GENERATIVE-AI-LEADER: NEW GOOGLE CLOUD CERTIFIED - GENERATIVE AI LEADER EXAM TEST SIMS

Free PDF 2025 Google Unparalleled Generative-AI-Leader: New Google Cloud Certified - Generative AI Leader Exam Test Sims

Free PDF 2025 Google Unparalleled Generative-AI-Leader: New Google Cloud Certified - Generative AI Leader Exam Test Sims

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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q15-Q20):

NEW QUESTION # 15
A highly regulated financial institution wants to use copyright 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 copyright?

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

Answer: A

Explanation:
copyright, 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.
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NEW QUESTION # 16
The office of the CISO wants to use generative AI (gen AI) to help automate tasks like summarizing case information, researching threats, and taking actions like creating detection rules. What agent should they use?

  • A. Customer service agent
  • B. Security agent
  • C. Code agent
  • D. Data agent

Answer: B

Explanation:
Given the tasks


NEW QUESTION # 17
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 role prompting.
  • C. Use few-shot prompting.
  • D. Use prompt chaining.

Answer: D

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 # 18
A company wants to use an AI agent to automate some tasks. They want everyone to understand the different functions of an AI agent. What is the function of an AI agent in the context of gen AI?

  • A. To provide the computational resources needed to train and run gen AI models.
  • B. To store and manage large datasets used for training and running gen AI models.
  • C. To provide a user-friendly interface for interacting with gen AI models.
  • D. To analyze situations, use multiple tools, and make informed decisions without requiring constant human input.

Answer: D

Explanation:
An AI agent, especially in the context of generative AI, is designed to be more autonomous and capable than a simple model. Its function is to understand a goal, analyze a situation, leverage various tools (including other generative AI models or external APIs), and make decisions or take actions to achieve that goal, often with minimal human intervention.
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NEW QUESTION # 19
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. Limit the chatbot's training data to prevent it from learning irrelevant information.
  • B. Use strict keyword matching to ensure that the chatbot only responds to specific commands.
  • C. Lower model temperature setting to produce more consistent and predictable responses.
  • D. Use prompt engineering techniques, like few-shot prompting, to provide the chatbot with examples of successful interactions.

Answer: D

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.
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NEW QUESTION # 20
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