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D-GAI-F-01퍼펙트최신버전공부자료100%유효한시험덤프자료

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EMC D-GAI-F-01 시험요강:

주제
소개

주제 1

• Ethics and Responsible AI: For all professionals working with AI, this section likely covers ethical considerations and responsible use of Generative AI in enterprise environments.

주제 2

• Introduction to Generative AI: For AI enthusiasts and IT professionals, this section of the exam likely covers the basic concepts and principles of Generative AI.

주제 3

• Use Cases and Applications: For business analysts and solution architects, this section might cover practical applications and use cases of Generative AI within Dell's ecosystem.

주제 4

• Dell's Generative AI Technologies: For Dell system administrators and AI implementers, this part of the exam probably focuses on Dell's specific implementations and tools related to Generative AI.

주제 5

• Implementation and Best Practices: For IT managers and system integrators, this part of the exam may address best practices for implementing Generative AI solutions using Dell technologies.

 

>> D-GAI-F-01퍼펙트 최신버전 공부자료 <<

D-GAI-F-01퍼펙트 최신버전 공부자료 덤프자료는 Dell GenAI Foundations Achievement 최고의 시험대비자료

네트웨크시대인 지금 인터넷에 검색하면 수많은EMC인증 D-GAI-F-01시험공부자료가 검색되는데 그중에서도ExamPassdump에서 출시한 EMC인증 D-GAI-F-01덤프가 가장 높은 인지도를 지니고 있습니다. EMC인증 D-GAI-F-01덤프에는EMC인증 D-GAI-F-01시험문제의 기출문제와 예상문제가 수록되어있어 덤프에 있는 문제만 잘 공부하시면 시험은 가볍게 패스가능합니다. EMC인증 D-GAI-F-01시험을 통과하여 자겨증취득하는 꿈에 더욱 가까이 다가가세요.

최신 Generative AI D-GAI-F-01 무료샘플문제 (Q28-Q33):

질문 # 28
A tech startup is developing a chatbot that can generate human-like text to interact with its users.
What is the primary function of the Large Language Models (LLMs) they might use?

• A. To store data
• B. To manage databases
• C. To encrypt information
• D. To generate human-like text

정답：D

설명：
Large Language Models (LLMs), such as GPT-4, are designed to understand and generate human-like text.
They are trained on vast amounts of text data, which enables them to produce responses that can mimic human writing styles and conversation patterns. The primary function of LLMs in the context of a chatbot is to interact with users by generating text that is coherent, contextually relevant, and engaging.
The Dell GenAI Foundations Achievement document outlines the role of LLMs in generative AI, which includes their ability to generate text that resembles human language1. This is essential for chatbots, as they are intended to provide a conversational experience that is as natural and seamless as possible.
Storing data (Option OA), encrypting information (Option OB), and managing databases (Option OD) are not the primary functions of LLMs. While LLMs may be used in conjunction with systems that perform these tasks, their core capability lies in text generation, making Option OC the correct answer.

 

질문 # 29
What are the three broad steps in the lifecycle of Al for Large Language Models?

• A. Preprocessing, Training, and Postprocessing
• B. Training, Customization, and Inferencing
• C. Initialization, Training, and Deployment
• D. Data Collection, Model Building, and Evaluation

정답：B

설명：
Training: The initial phase where the model learns from a large dataset. This involves feeding the model vast amounts of text data and using techniques like supervised or unsupervised learning to adjust the model's parameters.

 

질문 # 30
What are common misconceptions people have about Al? (Select two)

• A. Al is not prone to generate errors.
• B. Al can produce biased results.
• C. Al can learn from mistakes.
• D. Al can think like humans.

정답：D

설명：
There are several common misconceptions about AI. Here are two of the most prevalent:
Misconception: AI can think like humans.
Explanation:Many people believe that AI systems possess human-like thinking and understanding. However, AI, including advanced systems like neural networks, does not "think" in the human sense. AI operates based on complex algorithms and large datasets, processing information and making predictions or decisions based on patterns within the data.
Reality:AI lacks consciousness, emotions, and subjective experiences. It processes information syntactically rather than semantically, meaning it does not understand content in the way humans do.
References:
Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson.
Tegmark, M. (2017). Life 3.0: Being Human in the Age of Artificial Intelligence. Knopf.
Misconception: AI is not prone to generate errors.
Explanation:There is a belief that AI systems are infallible and do not make mistakes. This misconception stems from the high accuracy and efficiency of AI in specific tasks.
Reality:AI systems can and do make errors, often due to biases in training data, limitations in algorithms, or unexpected inputs. Errors can also arise from overfitting, underfitting, or adversarial attacks.
References:
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
Barocas, S., Hardt, M., & Narayanan, A. (2019).Fairness and Machine Learning.
fairmlbook.org.

 

질문 # 31
A team is looking to improve an LLM based on user feedback.
Which method should they use?

• A. Transfer Learning
• B. Reinforcement Learning through Human Feedback (RLHF)
• C. Self-supervised Learning
• D. Adversarial Training

정답：B

설명：
Reinforcement Learning through Human Feedback (RLHF) is a method that involves training machine learning models, particularly Large Language Models (LLMs), using feedback from humans. This approach is part of a broader category of machine learning known as reinforcement learning, where models learn to make decisions by receiving rewards or penalties.
In the context of LLMs, RLHF is used to fine-tune the models based on human preferences, corrections, and feedback. This process allows the model to align more closely with human values and produce outputs that are more desirable or appropriate according to human judgment.
The Dell GenAI Foundations Achievement document likely discusses the importance of aligning AI systems with human values and the various methods to improve AI models1. RLHF is particularly relevant for LLMs used in interactive applications like chatbots, where user satisfaction is a key metric.
Adversarial Training (Option OA) is typically used to improve the robustness of models against adversarial attacks. Self-supervised Learning (Option OC) involves models learning to understand data without explicit external labels. Transfer Learning (Option D) is about applying knowledge gained in one problem domain to a different but related domain. While these methods are valuable in their own right, they are not specifically focused on integrating human feedback into the training process, making Option OB the correct answer for improving an LLM based on user feedback.

 

질문 # 32
A startup is planning to leverage Generative Al to enhance its business.
What should be their first step in developing a Generative Al business strategy?

• A. Risk management
• B. Data management
• C. Investing in talent
• D. Identifying opportunities

정답：D

설명：
The first step for a startup planning to leverage Generative AI to enhance its business is to identify opportunities where this technology can be applied to create value. This involves understanding the business's goals and objectives and recognizing how Generative AI can complement existing workflows, enhance creative processes, and drive the company closer to achieving its strategic priorities1.
Identifying opportunities means assessing where Generative AI can have the most significant impact, whether it's in improving customer experiences, optimizing processes, or fostering innovation. It sets the foundation for a successful Generative AI strategy by aligning the technology's capabilities with the business's needs and goals1.
Investing in talent (Option OA), risk management (Option OB), and data management (Option OD) are also important steps in developing a Generative AI strategy. However, these steps typically follow after the opportunities have been identified. A clear understanding of the opportunities will guide the startup in making informed decisions about talent acquisition, risk assessment, and data governance necessary to support the chosen Generative AI applications23. Therefore, the correct first step is C. Identifying opportunities.

 

질문 # 33
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