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EMC Dell GenAI Foundations Achievement Sample Questions (Q50-Q55):
NEW QUESTION # 50
What is the purpose of the explainer loops in the context of Al models?
Answer: C
Explanation:
Explainer Loops: These are mechanisms or tools designed to interpret and explain the decisions made by AI models. They help users and developers understand the rationale behind a model's predictions.
NEW QUESTION # 51
What is the first step an organization must take towards developing an Al-based application?
Answer: C
Explanation:
The first step an organization must take towards developing an AI-based application is to develop a data strategy. The correct answer is option D. Here's an in-depth explanation:
Importance of Data:Data is the foundation of any AI system. Without a well-defined data strategy, AI initiatives are likely to fail because the model's performance heavily depends on the quality and quantity of data.
Components of a Data Strategy:A comprehensive data strategy includes data collection, storage, management, and ensuring data quality. It also involves establishing data governance policies to maintain data integrity and security.
Alignment with Business Goals:The data strategy should align with the organization's business goals to ensure that the AI applications developed are relevant and add value.
References:
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
Marr, B. (2017). Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things. Kogan Page Publishers.
NEW QUESTION # 52
A team is looking to improve an LLM based on user feedback.
Which method should they use?
Answer: D
Explanation:
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.
NEW QUESTION # 53
A legal team is assessing the ethical issues related to Generative Al.
What is a significant ethical issue they should consider?
Answer: D
Explanation:
When assessing the ethical issues related to Generative AI, a legal team should consider copyright and legal exposure as a significant concern. Generative AI has the capability to produce new content that could potentially infringe on existing copyrights or intellectual property rights. This raises complex legal questions about the ownership of AI-generated content and the liability for any copyright infringement that may occur as a result of using Generative AI systems.
The Official Dell GenAI Foundations Achievement document likely addresses the ethical considerations of AI, including the potential for bias and the importance of developing a culture to reduce bias and increase trust in AI systems1. Additionally, it would cover the ethical issues principles and the impact of AI in business, which includes navigating the legal landscape and ensuring compliance with copyright laws1.
Improved customer service (Option OA), enhanced creativity (Option OB), and increased productivity (Option OC) are generally viewed as benefits of Generative AI rather than ethical issues. Therefore, the correct answer is D. Copyright and legal exposure, as it pertains to the ethical and legal challenges that must be navigated when implementing Generative AI technologies.
NEW QUESTION # 54
A company is considering using deep neural networks in its LLMs.
What is one of the key benefits of doing so?
Answer: B
Explanation:
Deep neural networks (DNNs) are a class of machine learning models that are particularly well-suited for handling complex patterns and high-dimensional data. When incorporated into Large Language Models (LLMs), DNNs provide several benefits, one of which is their ability to handle more complicated problems.
Key Benefits of DNNs in LLMs:
* Complex Problem Solving: DNNs can model intricate relationships within data, making them capable of understanding and generating human-like text.
* Hierarchical Feature Learning: They learn multiple levels of representation and abstraction that help in identifying patterns in input data.
* Adaptability: DNNs are flexible and can be fine-tuned to perform a wide range of tasks, from translation to content creation.
* Improved Contextual Understanding: With deep layers, neural networks can capture context over longer stretches of text, leading to more coherent and contextually relevant outputs.
In summary, the key benefit of using deep neural networks in LLMs is their ability to handle more complicated problems, which stems from their deep architecture capable of learning intricate patterns and dependencies within the data. This makes DNNs an essential component in the development of sophisticated language models that require a nuanced understanding of language and context.
NEW QUESTION # 55
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