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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q15-Q20):
NEW QUESTION # 15
A company wants to choose a generative AI (gen AI) use case that will be successful and have the most impact. What key factor should they determine first according to Google Cloud-recommended practices?
- A. The availability of pre-trained models that are offered on various cloud computing platforms.
- B. The frequency of updates to the underlying foundation models used by different gen AI platforms.
- C. The specific business problems the company aims to solve and the desired outcomes.
- D. The number of employees who will be trained to use the new gen AI tools.
Answer: C
Explanation:
A fundamental principle for successful AI adoption, including generative AI, is to start with clear business problems and desired outcomes. Without a well-defined problem, the AI solution might not deliver meaningful value, regardless of the technology used. This "problem-first" approach is crucial for impactful AI strategy.
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NEW QUESTION # 16
A pharmaceutical company's research and development department spends significant time manually reviewing new scientific papers to identify potential drug targets. They need a solution that can answer questions about these documents and provide summarized insights to researchers without requiring extensive coding expertise. What should the organization do?
- A. Use Vertex AI AutoML to train a model that classifies papers into predefined research areas.
- B. Use Vertex AI Agent Builder to create a custom AI agent.
- C. Use Vertex AI Search to index the papers and enable keyword-based searches.
- D. Use Gemini for Google Workspace to facilitate collaborative document review.
Answer: B
Explanation:
The requirement is to answer questions about the documents and provide summarized insights without requiring extensive coding expertise. Vertex AI Agent Builder is designed precisely for creating custom AI agents, often with low-code or no-code capabilities, that can interact with and process large volumes of information like scientific papers. While Vertex AI Search could index papers for keyword searches, it doesn't directly answer questions or provide summarized insights in the same way a generative AI agent built with Agent Builder could. Gemini for Google Workspace is for collaborative work, not specifically for building custom AI agents for document analysis. Vertex AI AutoML is for training classification models, which is different from answering questions and summarizing.
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NEW QUESTION # 17
What is a primary benefit of using a multi-agent system?
- A. To serve as a platform for hosting traditional, non-AI applications.
- B. To simplify the most basic and repetitive rule-based tasks.
- C. To manage complex tasks that demand coordinated AI functions.
- D. To consolidate all unique AI functions into a single, undifferentiated model.
Answer: C
Explanation:
Multi-agent systems are designed to tackle complex problems by breaking them down into sub-tasks, where each agent specializes in a specific function. These agents then coordinate and collaborate to achieve a larger, more intricate goal that a single, monolithic AI model might struggle with.
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NEW QUESTION # 18
A software developer needs a highly efficient, open-source large language model that can be fine-tuned on a local machine for rapid prototyping of a chatbot application. They require a model that offers strong performance in natural language understanding and generation, while being lightweight enough to run on limited hardware. Which Google-developed family of models should they use?
- A. Imagen
- B. Gemini
- C. Veo
- D. Gemma
Answer: D
Explanation:
Gemma is Google's family of lightweight, state-of-the-art open models, built from the same research and technology used to create the Gemini3 models. They are designed for developers to build innovative AI applications on their local machines or in the cloud, offering a balance of performance and efficiency suitable for limited hardware and rapid prototyping. Veo is for video generation, Gemini is typically larger and more general-purpose, and Imagen is for image generation.
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NEW QUESTION # 19
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. Adjust the temperature parameter.
- B. Use prompt chaining.
- C. Use role prompting.
- 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 # 20
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