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| Section | Objectives |
|---|---|
| Topic 1: Google Cloud Generative AI Products and Tools | - Vertex AI and Gemini models overview - AI APIs and model deployment options on Google Cloud - Prompt design and prompt engineering tools |
| Topic 2: Business Applications and Adoption Strategy | - Identifying business use cases for generative AI - AI-driven transformation and workflow integration - Measuring ROI and value of generative AI initiatives |
| Topic 3: Fundamentals of Generative AI | - Difference between traditional AI, machine learning, and generative AI - Core concepts of generative AI and large language models - Key use cases and limitations of generative AI |
| Topic 4: Responsible AI and Governance | - Responsible AI principles and compliance - AI safety, bias, and fairness considerations - Data privacy and security in generative AI systems |
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질문 # 104
A team is using a generative AI model to automatically generate short summaries of customer feedback. They need to ensure that these summaries are concise and easy to digest. What model setting should they adjust?
정답：A
설명：
The objective is to make the generated summaries concise-that is, to control their length.
In the configuration of a generative AI model, particularly a large language model (LLM), the parameter used to directly control the maximum size of the response is the Output Length parameter (often referred to as max_output_tokens or max_tokens). By setting a low limit on this parameter, the team can ensure that the model is forced to terminate its response once that limit is reached, resulting in a shorter, more concise summary that is " easy to digest, " as requested.
The other parameters control different aspects of the output quality:
Temperature (C) controls the creativity or randomness of the output. Lowering it makes the output more predictable; raising it makes it more diverse. It does not control length.
Top-p (A) is a decoding method related to temperature that also controls the model ' s creativity by limiting the vocabulary from which it can choose the next token. It does not control length.
Safety settings (B) are used to filter and block the generation of harmful, illegal, or inappropriate content.
They do not affect the length or conciseness of the output.
(Reference: Google Cloud ' s Generative AI documentation on model parameters explicitly lists max_output_tokens or Output Length as the setting used to determine the maximum size of a model ' s generated response.)
질문 # 105
A user asks a generative AI model about the scientific accuracy of a popular science fiction movie. The model confidently states that humans can indeed travel faster than light, referencing specific but entirely fictional theories and providing made-up explanations of how this is achieved according to the movie's "established science." The model presents this information as factual, without indicating that it originates from a fictional work. What type of model limitation is this?
정답：C
질문 # 106
A research institution requires significant computational power and the ability to handle massive datasets efficiently. They are evaluating different cloud providers based on their infrastructure capabilities. What is a key benefit of using Google Cloud ' s AI-optimized infrastructure for this demanding workload?
정답：D
설명：
Google Cloud's AI-optimized infrastructure combines specialized accelerators, including TPUs and GPUs, with high-speed networking, scalable storage, and hypercomputer architecture. These components are designed to accelerate large-scale model training, inference, and data-intensive AI workloads while allowing organizations to scale resources according to demand. This directly benefits a research institution processing massive datasets and requiring substantial computational performance. Google Cloud does not guarantee that every project will be over-provisioned by a fixed factor or experience zero bottlenecks. It also does not provide unlimited free quantum-computing access. Although general-purpose virtual machines are available, the distinguishing advantage described in the question is specialized infrastructure optimized for AI rather than a primary focus on ordinary virtual machines. Therefore, enhanced performance and scalability through TPUs, GPUs, and hypercomputers is the correct benefit.
질문 # 107
A consumer electronics manufacturer is selecting a cloud platform to support an eight to twelve year roadmap for generative AI. Executives want a provider recognized for foundational AI breakthroughs that quickly become integrated services and purpose-built infrastructure. Which inherent strength of Google Cloud best aligns with these goals?
정답：B
설명：
This choice aligns with an eight to twelve year generative AI roadmap because Google consistently turns cutting edge research into widely available capabilities. Breakthroughs from Google Research become integrated services in Google Cloud such as managed model training, tuning, and deployment on Vertex AI. The company also builds purpose built infrastructure like Cloud TPU that is engineered for large scale training and inference. This pattern of research leadership that rapidly becomes productized gives organizations confidence that future advances in models, tooling, and hardware will arrive as usable cloud services.
질문 # 108
A retail company with a large online catalog wants to improve customer experience and drive sales by implementing multimodal search capabilities (image, voice, and text). What is a primary business benefit of this capability?
정답：A
설명：
Multimodal search directly enhances the customer experience by allowing them to find products using various intuitive methods (images, voice, text). This leads to easier product discovery, higher engagement, and ultimately increased customer satisfaction and potential sales, which is a primary business benefit.
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질문 # 109
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