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시험준비에가장좋은Generative-AI-Leader 100％시험패스공부자료덤프자료

우리사이트가 다른 덤프사이트보다 우수한 점은 바로 자료들이 모두 전면적이고 적중률과 정확입니다. 때문에 우리PassTIP를 선택함으로Google인증Generative-AI-Leader시험준비에는 최고의 자료입니다. 여러분이 성공을 위한 최고의 자료입니다.

Google Generative-AI-Leader 시험요강:

주제
소개

주제 1

Servicing AV Solutions: This section of the exam measures skills of an AV Maintenance Technician and focuses on maintaining and repairing AV systems. Tasks include supervising operations, conducting routine maintenance such as firmware updates and component replacements, and resolving issues through troubleshooting and repair processes, ensuring long-term system performance.

주제 2

Creating AV Solutions: This section of the exam measures the skills of an AV Systems Designer and covers the processes involved in understanding client requirements and translating them into practical AV solutions. It includes tasks such as conducting customer needs analysis, performing site surveys to evaluate conditions like lighting and acoustics, developing AV project scopes, and designing system layouts and documentation.

주제 3

Supporting AV System Operation: This section of the exam measures the skills of an AV Support Specialist and focuses on providing assistance in operating audiovisual systems. It includes remote and onsite troubleshooting, training users, and delivering live event support, ensuring systems function effectively in real-world usage scenarios.

주제 4

Implementing AV Solutions: This section of the exam measures the skills of an AV Integration Technician and focuses on turning AV system designs into reality. It assesses the ability to integrate systems by verifying components and managing supply installations, as well as handling documentation, training, and creating as-built schematics that support ongoing system operation.

>> Generative-AI-Leader 100％시험패스 공부자료 <<

Generative-AI-Leader시험덤프문제, Generative-AI-Leader최신 업데이트 인증덤프자료

Google Generative-AI-Leader인증시험은 전문적인 관련지식을 테스트하는 인증시험입니다. PassTIP는 여러분이Google Generative-AI-Leader인증시험을 통과할 수 잇도록 도와주는 사이트입니다. 여러분은 응시 전 저희의 문제와 답만 잘 장악한다면 빠른 시일 내에 많은 성과 가 있을 것입니다.

최신 Google Cloud Certified Generative-AI-Leader 무료샘플문제 (Q36-Q41):

질문 # 36
What does Vertex AI Search enable companies to do?

A. To ground LLM responses with first-party data, third-party data, and Google's knowledge graph.
B. To index and retrieve information from the entire public web, providing a comprehensive view of publicly available data.
C. To surface the most popular and frequently accessed content based on global user search patterns and trends.
D. To compare products from numerous online retailers, allowing users to find the best deals and product options across the internet.

정답：A

설명：
Vertex AI Search is designed to enable powerful search experiences over an organization's own data (first- party), external data (third-party), and can leverage Google's knowledge graph to provide more relevant and accurate responses, especially when grounding Large Language Models (LLMs). It does not index the entire public web like Google Search.
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질문 # 37
A company wants to use an AI agent to automate some tasks. They want everyone to understand the different functions of an AI agent. What is the function of an AI agent in the context of gen AI?

A. To store and manage large datasets used for training and running gen AI models.
B. To provide the computational resources needed to train and run gen AI models.
C. To provide a user-friendly interface for interacting with gen AI models.
D. To analyze situations, use multiple tools, and make informed decisions without requiring constant human input.

정답：D

설명：
An AI agent, especially in the context of generative AI, is designed to be more autonomous and capable than a simple model. Its function is to understand a goal, analyze a situation, leverage various tools (including other generative AI models or external APIs), and make decisions or take actions to achieve that goal, often with minimal human intervention.
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질문 # 38
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. Imagen
B. Veo
C. Gemini
D. Gemma

정답：D

설명：
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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질문 # 39
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 number of employees who will be trained to use the new gen AI tools.
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 availability of pre-trained models that are offered on various cloud computing platforms.

정답：B

설명：
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.
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질문 # 40
A company is developing an AI character for a video game. The AI character needs to learn how to navigate a complex environment and make decisions to achieve certain objectives within the game. When the AI takes actions that lead to positive outcomes, like finding a reward or overcoming an obstacle, it receives a positive score. When it takes actions that lead to negative outcomes, like hitting a wall or losing progress, it receives a negative score. Through this process of trial and error, the AI gradually improves the character's ability to play the game effectively. What machine learning should the company use?

A. Supervised learning
B. Unsupervised learning
C. Deep learning
D. Reinforcement learning

정답：D

설명：
This scenario perfectly describes reinforcement learning. In reinforcement learning, an agent learns to make decisions by interacting with an environment, receiving1 rewards for desirable actions and penalties for undesirable ones,2 and iteratively improving its behavior through trial and error to maximize cumulative reward.
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질문 # 41
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최근 더욱 많은 분들이Google인증Generative-AI-Leader시험에 도전해보려고 합니다. PassTIP에서는 여러분들의 시간돠 돈을 절약해드리기 위하여 저렴한 가격에 최고의 품질을 지닌 퍼펙트한Google인증Generative-AI-Leader시험덤플르 제공해드려 고객님의 시험준비에 편안함을 선물해드립니다. PassTIP제품을 한번 믿어보세요.

Generative-AI-Leader시험덤프문제: https://www.passtip.net/Generative-AI-Leader-pass-exam.html