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Generative-AI-Leader考古題分享 - Generative-AI-Leader考古题推薦

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Google Generative-AI-Leader 考試大綱：

主題
簡介

主題 1

Techniques to Improve Generative AI Model Output: This section of the exam measures the skills of AI Engineers and focuses on improving model reliability and performance. It introduces best practices to address common foundation model limitations such as bias, hallucinations, and data dependency, using methods like retrieval-augmented generation, prompt engineering, and human-in-the-loop systems. Candidates are also tested on different prompting techniques, grounding approaches, and the ability to configure model settings such as temperature and token count to optimize results.

主題 2

Fundamentals of Generative AI: This section of the exam measures the skills of AI Engineers and focuses on the foundational concepts of generative AI. It covers the basics of artificial intelligence, natural language processing, machine learning approaches, and the role of foundation models. Candidates are expected to understand the machine learning lifecycle, data quality, and the use of structured and unstructured data. The section also evaluates knowledge of business use cases such as text, image, code, and video generation, along with the ability to identify when and how to select the right model for specific organizational needs.

主題 3

Google Cloud’s Generative AI Offerings: This section of the exam measures the skills of Cloud Architects and highlights Google Cloud’s strengths in generative AI. It emphasizes Google’s AI-first approach, enterprise-ready platform, and open ecosystem. Candidates will learn about Google’s AI infrastructure, including TPUs, GPUs, and data centers, and how the platform provides secure, scalable, and privacy-conscious solutions. The section also explores prebuilt AI tools such as Gemini, Workspace integrations, and Agentspace, while demonstrating how these offerings enhance customer experience and empower developers to build with Vertex AI, RAG capabilities, and agent tooling.

主題 4

Business Strategies for a Successful Generative AI Solution: This section of the exam measures the skills of Cloud Architects and evaluates the ability to design, implement, and manage enterprise-level generative AI solutions. It covers the decision-making process for selecting the right solution, integrating AI into an organization, and measuring business impact. A strong emphasis is placed on secure AI practices, highlighting Google’s Secure AI Framework and cloud security tools, as well as the importance of responsible AI, including fairness, transparency, privacy, and accountability.

>> Generative-AI-Leader考古題分享 <<

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最新的 Google Cloud Certified Generative-AI-Leader 免費考試真題 (Q18-Q23):

問題 #18
A development team is configuring a generative AI model for a customer-facing application and wants to ensure the generated content is appropriate and harmless. What is the primary function of the safety settings parameter in a generative AI model?

A. To filter out potentially harmful or inappropriate content from the model's output based on the desired level of filtering.
B. To determine the number of tokens the model can process at once by influencing the complexity and length of inputs and outputs.
C. To limit the maximum text length that the model generates by ensuring concise responses.
D. To control the creativity and randomness of the model's output by adjusting the diversity of word choices.

答案：A

解題說明：
Safety settings in generative AI models are specifically designed to prevent the generation of content that could be harmful, offensive, or inappropriate. This includes filtering for categories like hate speech, sexually explicit content, self-harm, and violence, based on predefined thresholds. Options A, B, and D refer to other parameters like max_output_tokens or temperature, which control output length, input/output processing, and creativity, respectively, not safety.
________________________________________

問題 #19
What is the definition of generative AI?

A. A type of machine learning algorithm inspired by the human brain that is made up of interconnected nodes.
B. A type of artificial intelligence that enables a system to autonomously learn and improve using neural networks and deep learning.4
C. A type of artificial intelligence that can create new content and ideas, including text, images, music, and code.
D. A type of predictive model that estimates a relationship by fitting a line to the observed data.

答案：C

解題說明：
The defining characteristic of generative AI is its ability to create new, original content that resembles its training data. This includes various modalities like text, images, music, and code, rather than just classifying, predicting, or analyzing existing data.
________________________________________

問題 #20
What will Google Cloud's Agent Assist help a company achieve?

A. The ability to provide real-time assistance and recommended responses to live customer service agents during their interactions.
B. The ability to analyze conversational data to identify customer sentiment, common topics of discussion, and insights into agent performance and customer experience.
C. The ability to build and deploy deterministic and generative chatbot agents for automated customer support.
D. The infrastructure to provide an enterprise-grade contact center solution with omnichannel support, routing, and integration with CRM systems.

答案：A

解題說明：
Google Cloud's Agent Assist is specifically designed to augment human customer service agents. It provides real-time suggestions, retrieves relevant information, and offers recommended responses to agents during live interactions, improving their efficiency and consistency.
________________________________________

問題 #21
A marketing team wants to use a foundation model to create social media and advertising campaigns. They want to create written articles and images from text. They lack deep AI expertiseand need a versatile solution.
Which Google foundation model should they use?

A. Veo
B. Imagen
C. Gemma
D. Gemini

答案：D

解題說明：
Gemini is Google's most advanced and multimodal foundation model, capable of understanding and generating various forms of content, including text and images, from a single prompt. Its versatility makes it suitable for marketing teams that need to create diverse campaign materials without deep AI expertise.
Imagen is specifically for image generation, Gemma is a family of smaller, open models, and Veo is for video generation.
________________________________________

問題 #22
A human resources team is implementing a new generative AI application to assist the department in screening a large volume of job applications. They want to ensure fairness and build trust with potential candidates. What should the team prioritize?

A. Ensuring AI operates transparently, especially regarding application evaluation and data usage.
B. Focusing on minimizing the processing time for each application to improve efficiency.
C. Ensuring that the AI application can automatically rank all candidates without requiring human review.
D. Integrating the AI application with various job boards to maximize candidate reach.

答案：A

解題說明：
To ensure fairness and build trust, especially in sensitive areas like job applications, transparency in how AI evaluates applications and uses data is paramount. This involves understanding potential biases, explaining decisions (where possible), and ensuring human oversight.
________________________________________

問題 #23
......

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