Google
Generative-AI-Leader
Google Cloud Certified - Generative AI Leader Exam
Exam Version: 6.4
Questions & Answers PDF
(Demo Version - Limited Content)
For More Information - Visit link below:
https://p2pexam.com/generative-ai-leader
, Question 1. (Single Select)
A logistics company wants to use a generative AI (gen AI) agent to automatically check real-time inventory
levels across its warehouses and adjust delivery schedules. The gen AI agent needs access to internal
inventory data. They want the most cost-effective solution. What should the organization do?
A: Build a custom API instead of using the gen AI agent.
B: Use pre-built gen AI chatbots for inventory questions.
C: Use Vertex AI Studio to fine-tune a model with sample inventory data.
D: Use Google Cloud databases and Vertex AI for the agent to get live data.
Answer: D
Explanation:
To achieve real-time inventory checks and adjust delivery schedules, the generative AI agent needs live
access to the company's internal inventory data. Google Cloud databases provide the structured storage
for this data, and Vertex AI offers the platform to build, deploy, and manage the AI agent, including
connecting it to these live data sources. This approach allows the agent to make informed decisions based
on current information. Building a custom API for every interaction might be less cost-effective in the long
run for dynamic inventory data. Pre-built chatbots might not have the direct integration needed for real-time
adjustments, and fine-tuning with sample data wouldn't provide the live data access required.
Question 2. (Single Select)
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
criteri
a. Why is this an inappropriate use case for Gemini?
A: Gemini cannot integrate with required financial databases.
B: Gemini is not equipped to handle structured numerical data for financial assessments.
C: Gemini is designed for flexible content generation and inference, not rigid rule-based decisions.
D: Gemini deployment for this scenario would be too expensive and complex.
Answer: C
https://p2pexam.com/generative-ai-leader Page 2 of 5
Generative-AI-Leader
Google Cloud Certified - Generative AI Leader Exam
Exam Version: 6.4
Questions & Answers PDF
(Demo Version - Limited Content)
For More Information - Visit link below:
https://p2pexam.com/generative-ai-leader
, Question 1. (Single Select)
A logistics company wants to use a generative AI (gen AI) agent to automatically check real-time inventory
levels across its warehouses and adjust delivery schedules. The gen AI agent needs access to internal
inventory data. They want the most cost-effective solution. What should the organization do?
A: Build a custom API instead of using the gen AI agent.
B: Use pre-built gen AI chatbots for inventory questions.
C: Use Vertex AI Studio to fine-tune a model with sample inventory data.
D: Use Google Cloud databases and Vertex AI for the agent to get live data.
Answer: D
Explanation:
To achieve real-time inventory checks and adjust delivery schedules, the generative AI agent needs live
access to the company's internal inventory data. Google Cloud databases provide the structured storage
for this data, and Vertex AI offers the platform to build, deploy, and manage the AI agent, including
connecting it to these live data sources. This approach allows the agent to make informed decisions based
on current information. Building a custom API for every interaction might be less cost-effective in the long
run for dynamic inventory data. Pre-built chatbots might not have the direct integration needed for real-time
adjustments, and fine-tuning with sample data wouldn't provide the live data access required.
Question 2. (Single Select)
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
criteri
a. Why is this an inappropriate use case for Gemini?
A: Gemini cannot integrate with required financial databases.
B: Gemini is not equipped to handle structured numerical data for financial assessments.
C: Gemini is designed for flexible content generation and inference, not rigid rule-based decisions.
D: Gemini deployment for this scenario would be too expensive and complex.
Answer: C
https://p2pexam.com/generative-ai-leader Page 2 of 5
