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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:

Margurite
22 days ago
I bet the exam writer is hoping we don't get too 'un-supervised' with our answers!
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Micaela
23 days ago
I can't believe they're testing us on this! Supervised and unsupervised learning are like the pepperoni and pineapple of the AI world - you either love 'em or you hate 'em.
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Eliz
2 days ago
A) Supervised learning feeds a large corpus of raw data into the AI system, while unsupervised learning uses labeled data to teach the AI system what output is expected.
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Nickie
25 days ago
Hmm, this is a tough one. I'm going to go with D just to be different. Hey, maybe the exam writer was feeling a bit unsupervised when they wrote this question!
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Stefan
11 hours ago
User 1: I think the answer is A.
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Simona
1 months ago
I'm torn between B and C, but I think C is the way to go. Supervised and unsupervised learning are like the yin and yang of AI training.
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Allene
10 days ago
I agree, supervised learning is more focused on teaching the AI system based on labeled data.
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Lorita
21 days ago
I think C is the correct answer. Supervised learning uses labeled data to teach the AI system what output is expected.
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Henriette
1 months ago
Option C is clearly the correct answer. Supervised learning uses labeled data, while unsupervised learning uses raw data. It's as simple as that!
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Ardella
2 months 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 months ago
I believe supervised learning uses labeled data to teach the AI system what output is expected.
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Ardella
2 months ago
I think the difference lies in how the AI system is trained.
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