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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q26-Q31):
NEW QUESTION # 26
A global news agency is developing a generative AI tool to quickly summarize breaking newsarticles as they emerge online. The goal is to provide their audience with rapid updates on fast-developing stories from various global sources. What Google Cloud solution should they use?
- A. Vertex AI Natural Language API
- B. BigQuery
- C. Document AI
- D. Grounding with Google Search
Answer: D
Explanation:
For summarizing breaking news articles as they emerge online from various global sources, the generative AI model needs access to current, broad, and rapidly updating information. Grounding with Google Search allows the LLM to pull in the latest information from the web, ensuring the summaries are current and comprehensive. While Vertex AI Natural Language API can summarize text, it wouldn't inherently have access to the latest breaking news unless explicitly fed.
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NEW QUESTION # 27
A company wants a generative AI platform that provides the infrastructure, tools, and pre-trained models needed to build, deploy, and manage its generative AI solutions. Which Google Cloud offering should the company use?
- A. Google Cloud Storage
- B. BigQuery
- C. Vertex AI
- D. Google Kubernetes Engine (GKE)
Answer: C
Explanation:
Vertex AI is Google Cloud's unified machine learning platform that provides end-to-end support for the ML lifecycle, including access to pre-trained models (foundation models), tools for fine-tuning, deployment, and management of generative AI solutions. BigQuery is a data warehouse, GKE is for container orchestration, and Cloud Storage is for object storage; while they might be components used with Vertex AI, they are not the comprehensive generative AI platform themselves.
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NEW QUESTION # 28
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. Gemini
- B. Imagen
- 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 # 29
What is a characteristic of Google Cloud as a generative AI company?
- A. Google Cloud ensures that all generative AI models and data are completely secured and isolated from external networks.
- B. Google Cloud provides fully autonomous AI agents that require zero configuration or management overhead.
- C. Google Cloud has an AI-first focus that enables innovation, with continuous updates and broad integration across its platform.
- D. Google Cloud relies on proprietary, closed-source AI technologies for maximum security benefits.
Answer: C
Explanation:
Google Cloud emphasizes an AI-first approach, integrating AI capabilities across its services and consistently innovating with new models and features. While security is a high priority, fully autonomous AI agents requiring zero configuration are generally not the norm, and "completely secured and isolated from external networks" is an oversimplification of cloud security models. Google also contributes to and supports open- source AI initiatives, not solely relying on proprietary closed-source technologies.
________________________________________
NEW QUESTION # 30
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 allow the development team to train a single foundation model on all company documents.
- B. They enable the generative AI model to retrieve the most up-to-date and relevant information from the policy documents in real-time.
- C. They provide a pre-built user interface for the chatbot, simplifying the front-end development process.
- D. They automatically create summaries of all company policies, which are then presented to employees as quick answers.
Answer: B
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.
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NEW QUESTION # 31
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Before joining Foundstone, Mike was a freelance consultant and developer of Generative-AI-Leader Web-based information systems, working with clients such as The Economist, the London transport authority, and various United Kingdom universities.
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