Generative-AI-Leader 試験問題を無料オンラインアクセス

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 specific business problems the company aims to solve and the desired outcomes.
• C.The frequency of updates to the underlying foundation models used by different gen AI platforms.
• D.The number of employees who will be trained to use the new gen AI tools.

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 enable the generative AI model to retrieve the most up-to-date and relevant information from the policy documents in real-time.
• B.They automatically create summaries of all company policies, which are then presented to employees as quick answers.
• C.They provide a pre-built user interface for the chatbot, simplifying the front-end development process.
• D.They allow the development team to train a single foundation model on all company documents.

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 deployment for this scenario would be too expensive and complex.
• B.Gemini is designed for flexible content generation and inference, not rigid rule-based decisions.
• C.Gemini cannot integrate with required financial databases.
• D.Gemini is not equipped to handle structured numerical data for financial assessments.

A company is developing a generative AI-powered customer support chatbot. They want to ensure the chatbot can answer a wide range of customer questions accurately, even those related to recently updated product information not present in the model's original training dat a. What is a key benefit of implementing retrieval-augmented generation (RAG) in this chatbot?

• A.RAG will significantly reduce the computational resources required to run the generative AI model.
• B.RAG will enable the chatbot to fine-tune its underlying language model on the fly based on customer interactions.
• C.RAG will primarily help the chatbot generate more creative and engaging conversational responses.
• D.RAG will enable the chatbot to access and utilize external, up-to-date knowledge sources to provide more accurate and relevant answers.

A national bank is overwhelmed by customer inquiries across multiple channels and needs an AI-powered solution to provide seamless, consistent support, empower customer support agents, and improve service quality. What Google Cloud product should the bank use?

• A.Gemini for Google Workspace
• B.Gemini for Google Cloud
• C.Google Contact Center as a Service
• D.Vertex AI Search