CUSTOMIZED GENERATIVE-AI-LEADER LAB SIMULATION & GENERATIVE-AI-LEADER TRAINING COURSES

Customized Generative-AI-Leader Lab Simulation & Generative-AI-Leader Training Courses

Customized Generative-AI-Leader Lab Simulation & Generative-AI-Leader Training Courses

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Tags: Customized Generative-AI-Leader Lab Simulation, Generative-AI-Leader Training Courses, Generative-AI-Leader Guide, Generative-AI-Leader Free Exam Dumps, Reliable Generative-AI-Leader Exam Bootcamp

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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q34-Q39):

NEW QUESTION # 34
A software development team wants to use generative AI (gen AI) to code faster so they can launch their software prototype quicker. What should the team do?

  • A. Use gen AI to identify potential bugs and security vulnerabilities in their code.
  • B. Use gen AI to suggest code snippets and complete functions.
  • C. Use gen AI to automatically generate comprehensive documentation for their code.
  • D. Use gen AI to refactor and optimize existing code.

Answer: B

Explanation:
While generative AI can assist with all the options listed (refactoring, documentation, bug identification), its most direct and significant impact on coding faster for a prototype is through code generation. Suggesting code snippets and completing functions directly accelerates the writing of new code, enabling quicker prototyping.
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NEW QUESTION # 35
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 prompt engineering techniques, like few-shot prompting, to provide the chatbot with examples of successful interactions.
  • C. Use strict keyword matching to ensure that the chatbot only responds to specific commands.
  • D. Lower model temperature setting to produce more consistent and predictable responses.

Answer: B

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 # 36
A social media platform uses a generative AI model to automatically generate summaries of user-submitted posts to provide quick overviews for other users. While the summaries are generally accurate for factual posts, the model occasionally misinterprets sarcasm, satire, or nuanced opinions, leading to summaries that misrepresent the original intent and potentially cause misunderstandings or offense among users. What should the platform do to overcome this limitation of the AI-generated summaries?

  • A. Incorporate a human-in-the-loop (HITL) review process to refine the summaries.
  • B. Implement stricter safety settings to filter out potentially misinterpreted content altogether.
  • C. Increase the temperature parameter of the model to encourage more varied and less literal interpretations.
  • D. Decrease the output length of the summaries to make them more concise.

Answer: A

Explanation:
When AI struggles with nuances like sarcasm or satire, human oversight is often the most effective solution.
A human-in-the-loop (HITL) process allows human reviewers to check, correct, and refine AI-generated content before it is published, ensuring accuracy and appropriateness, especially for sensitive or complex language.
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NEW QUESTION # 37
An organization wants granular control over who can use and see their generative AI models and related resources on Google Cloud. Which Google Cloud security offering is specifically for this purpose?

  • A. Identity and Access Management
  • B. Workload monitoring tools
  • C. Security Command Center
  • D. Secure-by-design infrastructure

Answer: A

Explanation:
Identity and Access Management (IAM) is the fundamental Google Cloud service that allows you to define who has what access to which resources. It provides granular control over permissions for users, groups, and service accounts, including access to generative AI models and related data.
________________________________________


NEW QUESTION # 38
A large e-commerce company with a vast and frequently updated product catalog finds that customers struggle to find products on their website, and support agents spend too much time finding detailed product information. The company wants to improve search accuracy and efficiency for both customers and support.
What Google Cloud solution should they use?

  • A. Vertex AI Model Garden
  • B. Vertex AI Natural Language API
  • C. Pre-built RAG with Vertex AI Search
  • D. Vertex AI Conversation

Answer: C

Explanation:
This scenario strongly points to the need for accurate and up-to-date information retrieval from a product catalog. Pre-built RAG (Retrieval-Augmented Generation) combined with Vertex AI Search is the ideal solution. Vertex AI Search can index the product catalog, and RAG can then use thisindexed data to ground the responses of a generative AI model, ensuring that both customer searches and support agent queries retrieve precise and relevant product information.
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NEW QUESTION # 39
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