Google passcert generative-ai-leader Vce Exam Download by Saint q5 vce pdf

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Google Generative-AI-Leader Exam Overview :

Exam Name:	Google Cloud Certified - Generative AI Leader Exam
Exam Code:	Generative-AI-Leader Dumps
Vendor:	Google	Certification:	Google Cloud Certified
Questions:	74 Q&A's	Shared By:	saint

Question 20

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 the chatbot's ability to understand and respond effectively to user prompts?

Options:

Use prompt engineering techniques, like few-shot prompting, to provide the chatbot with examples of successful interactions.

Limit the chatbot's training data to prevent it from learning irrelevant information.

Use strict keyword matching to ensure that the chatbot only responds to specific commands.

Lower model temperature setting to produce more consistent and predictable responses.

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Question 21

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?

Options:

Implement stricter safety settings to filter out potentially misinterpreted content altogether.

Increase the temperature parameter of the model to encourage more varied and less literal interpretations.

Decrease the output length of the summaries to make them more concise.

Incorporate a human-in-the-loop (HITL) review process to refine the summaries.

Discussion

Question 22

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?

Options:

Gemini cannot integrate with required financial databases.

Gemini is not equipped to handle structured numerical data for financial assessments.

Gemini is designed for flexible content generation and inference, not rigid rule-based decisions.

Gemini deployment for this scenario would be too expensive and complex.