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Dell EMC D-GAI-F-01 Exam Questions
- Topic 1: 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.
- Topic 2: 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.
- Topic 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.
- Topic 4: 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.
- Topic 5: 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.
Free Dell EMC D-GAI-F-01 Exam Actual Questions
Note: Premium Questions for D-GAI-F-01 were last updated On Feb. 27, 2025 (see below)
What is feature-based transfer learning?
Feature-based transfer learning involves leveraging certain features learned by a pre-trained model and adapting them to a new task. Here's a detailed explanation:
Feature Selection: This process involves identifying and selecting specific features or layers from a pre-trained model that are relevant to the new task while discarding others that are not.
Adaptation: The selected features are then fine-tuned or re-trained on the new dataset, allowing the model to adapt to the new task with improved performance.
Efficiency: This approach is computationally efficient because it reuses existing features, reducing the amount of data and time needed for training compared to starting from scratch.
Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359.
Yosinski, J., Clune, J., Bengio, Y., & Lipson, H. (2014). How Transferable Are Features in Deep Neural Networks? In Advances in Neural Information Processing Systems.
A company is implementing governance in its Generative Al.
What is a key aspect of this governance?
Governance in Generative AI involves several key aspects, among which transparency is crucial. Transparency in AI governance refers to the clarity and openness regarding how AI systems operate, the data they use, the decision-making processes they employ, and the way they are developed and deployed. It ensures that stakeholders understand AI processes and can trust the outcomes produced by AI systems.
User interface design (Option OB), speed of deployment (Option OC), and cost efficiency (Option OD) are important factors in the development and implementation of AI systems but are not specifically governance aspects. Governance focuses on the overarching principles and practices that guide the ethical and responsible use of AI, making transparency the key aspect in this context.
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?
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.
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.
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 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?
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.
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.
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