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質問 # 106
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?
正解：B
解説：
According to Google ' s principles for successful AI adoption, organizations should adopt a " problem-first " approach to ensure their investments deliver measurable value. The strategic choice of a use case should always be motivated by a clear business imperative.
Determining the specific business problems and desired outcomes (B) is the foundational step in any successful Gen AI strategy. Without a well-defined problem (e.g., " reduce customer response time by 30% " ) and a measurable desired outcome (e.g., " increase customer satisfaction scores " ), any AI solution runs the risk of being a technology in search of a purpose, leading to limited adoption or failure to deliver meaningful ROI.
Options A, C, and D are considerations secondary to the initial strategic alignment:
Availability of models (C) only dictates the technical feasibility, not the business value.
Training employees (A) is a resource requirement, not the goal itself.
Model updates (D) is a technical concern related to model longevity, not the primary strategic driver for use case selection.
The priority is always to align the AI solution with high-value business objectives.
(Reference: Google Cloud Generative AI strategy guidelines state: " 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. " )
質問 # 107
What is a definition of an AI agent?
正解：C
解説：
In the generative AI landscape, an AI Agent is distinct from a basic chatbot or standard foundation model because of its ability to act autonomously to execute multi-step objectives.
The correct definition is an application that learns how to achieve a goal based on inputs and tools available to it (C). An agent is built around a core Large Language Model (LLM) which serves as its "brain." Given an objective or goal from a user, the agent uses a reasoning loop (such as ReAct) to evaluate inputs, break the goal into sub-tasks, and call external tools (like APIs, web search, databases, or calculators) to interact with the external world and accomplish the task.
Option A is incorrect because agents are dynamic and action-oriented, not static.
Option B describes a "Human-in-the-loop" supervisor, not the AI agent itself.
Option D describes a chat interface or frontend wrapper, which is merely a way to communicate with an agent, not the definition of the agent's functional architecture.
(Reference: Google Cloud's official architecture guides for Generative AI define an Agent as an autonomous software entity driven by an LLM that accepts natural language goals, breaks them down into executable workflows, and leverages tools to alter states or retrieve information to satisfy that goal.)
質問 # 108
An animation studio needs to swiftly produce brief animated cartoons based on written descriptions of scenes and character actions. They want to preview their animated storyboards and obtain rapid feedback on the story and flow. Why should they use Veo for this task?
正解：B
解説：
Veo is Google's generative video model and is designed to create video content from natural-language prompts and visual inputs such as still images. The animation studio can describe scenes, character actions, camera movement, and visual style, then use Veo to generate short video sequences for storyboard visualization. This dramatically accelerates early creative experimentation and allows the team to assess pacing, story flow, and visual direction before investing in full production. Speech generation is associated with audio or text-to-speech models, not Veo's central capability. Producing application code is a coding- model use case, while describing Veo merely as a lightweight customizable model does not address the video- generation requirement. Therefore, Veo's optimization for producing video from written descriptions and still pictures directly matches the studio's objective.
質問 # 109
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?
正解：B
解説：
According to Google's principles for successful AI adoption, organizations should adopt a
"problem-first" approach to ensure their investments deliver measurable value. The strategic choice of a use case should always be motivated by a clear business imperative. Determining the specific business problems and desired outcomes (B) is the foundational step in any successful Gen AI strategy. Without a well-defined problem (e.g., "reduce customer response time by 30%") and a measurable desired outcome (e.g., "increase customer satisfaction scores"), any AI solution runs the risk of being a technology in search of a purpose, leading to limited adoption or failure to deliver meaningful ROI.
質問 # 110
What is a characteristic of Google Cloud as a generative AI company?
正解：B
解説：
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.
質問 # 111
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