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EMC Dell GenAI Foundations Achievement Sample Questions (Q10-Q15):

NEW QUESTION # 10
What is Transfer Learning in the context of Language Model (LLM) customization?

A. It is a process where the model is additionally trained on something like human feedback.
B. It is where you can adjust prompts to shape the model's output without modifying its underlying weights.
C. It is where purposefully malicious inputs are provided to the model to make the model more resistant to adversarial attacks.
D. It is a type of model training that occurs when you take a base LLM that has been trained and then train it on a different task while using all its existing base weights.

Answer: D

Explanation:
Transfer learning is a technique in AI where a pre-trained model is adapted for a different but related task.
Here's a detailed explanation:
Transfer Learning:This involves taking a base model that has been pre-trained on a large dataset and fine-tuning it on a smaller, task-specific dataset.
Base Weights:The existing base weights from the pre-trained model are reused and adjusted slightly to fit the new task, which makes the process more efficient than training a model from scratch.
Benefits:This approach leverages the knowledge the model has already acquired, reducing the amount of data and computational resources needed for training on the new task.
References:
Tan, C., Sun, F., Kong, T., Zhang, W., Yang, C., & Liu, C. (2018).A Survey on Deep Transfer Learning. In International Conference on Artificial Neural Networks.
Howard, J., & Ruder, S. (2018). Universal Language Model Fine-tuning for Text Classification.
In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

NEW QUESTION # 11
What impact does bias have in Al training data?

A. It ensures faster processing of data by the model.
B. It simplifies the algorithm's complexity.
C. It enhances the model's performance uniformly across tasks.
D. It can lead to unfair or incorrect outcomes.

Answer: D

Explanation:
Definition of Bias: Bias in AI refers to systematic errors that can occur in the model due to prejudiced assumptions made during the data collection, model training, or deployment stages.

NEW QUESTION # 12
Whatrole does human feedback play in Reinforcement Learning for LLMs?

A. It is used to provide real-time corrections to the model's output.
B. It helps in identifying the model's architecture for optimization.
C. It assists in the physical hardware improvement of the model.
D. It rewards good output and penalizes bad output to improve the model.

Answer: D

Explanation:
Role of Human Feedback: In reinforcement learning for LLMs, human feedback is used to fine-tune the model by providing rewards for correct outputs and penalties for incorrect ones. This feedback loop helps the model learn more effectively.

NEW QUESTION # 13
A company is planning its resources for the generative Al lifecycle.
Which phase requires the largest amount of resources?

A. Training
B. Fine-tuning
C. Inferencing
D. Deployment

Answer: A

Explanation:
The training phase of the generative AI lifecycle typically requires the largest amount of resources. This is because training involves processing large datasets to create models that can generate new data or predictions.
It requires significant computational power and time, especially for complex models such as deep learning neural networks. The resources needed include data storage, processing power (often using GPUs or specialized hardware), and the time required for the model to learn from the data.
In contrast, deployment involves implementing the model into a production environment, which, while important, often does not require as much resource intensity as the training phase. Inferencing is the process where the trained model makes predictions, which does require resources but not to the extent of the training phase. Fine-tuning is a process of adjusting a pre-trained model to a specific task, which also uses fewer resources compared to the initial training phase.
The Official Dell GenAI Foundations Achievement document outlines the importance of understanding the concepts of artificial intelligence, machine learning, and deep learning, as well as the scope and need of AI in business today, which includes knowledge of the generative AI lifecycle1.

NEW QUESTION # 14
A business wants to protect user data while using Generative Al.
What should they prioritize?

A. Robust security measures
B. Customer feedback
C. Marketing strategies
D. Product innovation

Answer: A

Explanation:
When a business is using Generative AI and wants to ensure the protection of user data, the top priority should be robust security measures. This involves implementing comprehensive data protection strategies, such as encryption, access controls, and secure data storage, to safeguard sensitive information against unauthorized access and potential breaches.
The Official Dell GenAI Foundations Achievement document underscores the importance of security in AI systems. It highlights that while Generative AI can provide significant benefits, it is crucial to maintain the confidentiality, integrity, and availability of user data12. This includes adhering to best practices for data security and privacy, which are essential for building trust and ensuring compliance with regulatory requirements.
Customer feedback (Option OA), product innovation (Option OB), and marketing strategies (Option OC) are important aspects of business operations but do not directly address the protection of user data. Therefore, the correct answer is D. Robust security measures, as they are fundamental to the ethical and responsible use of AI technologies, especially when handling sensitive user data.

NEW QUESTION # 15
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EMC Dell GenAI Foundations Achievement Sample Questions (Q10-Q15):

100% Pass D-GAI-F-01 - Dell GenAI Foundations Achievement Updated VCE Exam Simulator

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