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Dell EMC Exam D-GAI-F-01 Topic 4 Question 13 Discussion

Actual exam question for Dell EMC's D-GAI-F-01 exam
Question #: 13
Topic #: 4
[All D-GAI-F-01 Questions]

What is the difference between supervised and unsupervised learning in the context of training Large Language Models (LLMs)?

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Suggested Answer: A

Mitigating biases in Generative AI is a complex challenge that requires a multifaceted approach. One effective strategy is to conduct regular audits of the AI systems and the data they are trained on. These audits can help identify and address biases that may exist in the models. Additionally, incorporating diverse perspectives in the development process is crucial. This means involving a team with varied backgrounds and viewpoints to ensure that different aspects of bias are considered and addressed.

The Dell GenAI Foundations Achievement document emphasizes the importance of ethics in AI, including understanding different types of biases and their impacts, and fostering a culture that reduces bias to increase trust in AI systems12. It is likely that the document would recommend regular audits and the inclusion of diverse perspectives as part of a comprehensive strategy to mitigate biases in Generative AI.

Focusing on one language for training data (Option B), ignoring systemic biases (Option C), or using a single perspective during model development (Option D) would not be effective in mitigating biases and, in fact, could exacerbate them. Therefore, the correct answer is A. Regular audits and diverse perspectives.


Contribute your Thoughts:

Ardella
1 days ago
That makes sense. So unsupervised learning must rely on raw data to determine the appropriate weights in its neural network.
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Ashton
2 days ago
I believe supervised learning uses labeled data to teach the AI system what output is expected.
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Ardella
7 days ago
I think the difference lies in how the AI system is trained.
upvoted 0 times
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