GENERATIVE-AI-LEADER REAL SHEETS | VALID GENERATIVE-AI-LEADER VCE

Generative-AI-Leader Real Sheets | Valid Generative-AI-Leader Vce

Generative-AI-Leader Real Sheets | Valid Generative-AI-Leader Vce

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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q36-Q41):

NEW QUESTION # 36
A company wants to use generative AI to create a chatbot that can answer customer questions about their products and services. They need to ensure that the chatbot only uses information from the company's official documentation. What should the company do?

  • A. Use role prompting.
  • B. Adjust the temperature parameter.
  • C. Use prompt chaining.
  • D. Use grounding.

Answer: D

Explanation:
Grounding is the technique of "grounding" the LLM's responses in specific, authoritative data sources (like the company's official documentation). This prevents the model from "hallucinating" or providing information outside of the approved knowledge base, ensuring accuracy and relevance to the company's specific products and services.
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NEW QUESTION # 37
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. Data agent
  • C. Code agent
  • D. Security agent

Answer: D

Explanation:
Given the tasks involve researching threats and creating detection rules, the most appropriate and specialized agent would be a Security agent. This type of agent would be pre-configured or easily adaptable to understand security-specific contexts, data, and actions within a CISO's domain.
________________________________________


NEW QUESTION # 38
A development team is building an internal knowledge base chatbot to answer employee questions about company policies and procedures. This information is stored across various documents in Google Cloud Storage and is updated regularly by different departments. What is the primary benefit of using Google Cloud's RAG APIs in this scenario?

  • A. They automatically create summaries of all company policies, which are then presented to employees as quick answers.
  • B. They provide a pre-built user interface for the chatbot, simplifying the front-end development process.
  • C. They allow the development team to train a single foundation model on all company documents.
  • D. They enable the generative AI model to retrieve the most up-to-date and relevant information from the policy documents in real-time.

Answer: D

Explanation:
The primary benefit of RAG (Retrieval-Augmented Generation) in this context is its ability to ensure the chatbot provides accurate and up-to-date information. By retrieving relevant and recent policy documents from Cloud Storage in real-time and then grounding the LLM's response with this information, the chatbot avoids hallucinating or providing outdated answers, which is crucial for an internal knowledge base.
________________________________________


NEW QUESTION # 39
A company is exploring Google Agentspace to improve how its employees search for information on their enterprise systems and automate certain tasks. What is the key business advantage of using Agentspace?

  • A. Improved productivity and data interaction using AI assistants and advanced document analysis.
  • B. More granular control over support team access and permissions for sensitive data.
  • C. Enhanced real-time communication and collaboration among team members.
  • D. Greater interoperability with legacy software systems and databases.

Answer: A

Explanation:
Google Agentspace (or similar agent platforms) is designed to empower employees with AI-powered assistants that can navigate and interact with enterprise systems, analyze documents, and automate tasks. This directly leads to improved employee productivity and more efficient data interaction by leveraging AI to streamline workflows and provide faster access to information.


NEW QUESTION # 40
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 analyze situations, use multiple tools, and make informed decisions without requiring constant human input.
  • C. To store and manage large datasets used for training and running gen AI models.
  • D. To provide a user-friendly interface for interacting with gen AI models.

Answer: B

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.
________________________________________


NEW QUESTION # 41
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