Free Dell EMC NCA-GENL Exam Questions
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Dell EMC NCA-GENL Exam Questions
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Provided By: Dell EMC
- Exam: NCA - Generative AI LLMs
- Certification: NVIDIA Certified Associate
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Total Questions: 300
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Updated On: Feb 17, 2025
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Rated: 4.9 |
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Online Users: 600
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Question 1
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You are working on deploying a Large Language Model (LLM) for a financial institution where it needs to generate detailed reports based on user inputs. The LLM occasionally generates responses that are logically correct but irrelevant to the user's query. The senior team member suggests a modification in the model’s attention mechanism to improve relevance. What adjustment to the attention mechanism would most likely improve the relevance of the LLM’s responses?
Answer: A
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You are working on deploying a Large Language Model (LLM) for a financial institution where it needs to generate detailed reports based on user inputs. The LLM occasionally generates responses that are logically correct but irrelevant to the user's query. The senior team member suggests a modification in the model’s attention mechanism to improve relevance. What adjustment to the attention mechanism would most likely improve the relevance of the LLM’s responses?
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Question 2
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You are developing a machine learning model for predictive maintenance in a manufacturing plant. The model needs to analyze sensor data from thousands of machines in real-time, identifying patterns that indicate potential failures. This requires processing a continuous stream of data, some of which exceeds the available memory capacity. Which approach is most suitable for handling this complex scenario?
Answer: A
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You are developing a machine learning model for predictive maintenance in a manufacturing plant. The model needs to analyze sensor data from thousands of machines in real-time, identifying patterns that indicate potential failures. This requires processing a continuous stream of data, some of which exceeds the available memory capacity. Which approach is most suitable for handling this complex scenario?
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Question 3
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During the evaluation of a deployed LLM model, you notice that the model’s response times are inconsistent, with significant delays occurring sporadically. What is the most likely cause of these performance fluctuations?
Answer: D
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During the evaluation of a deployed LLM model, you notice that the model’s response times are inconsistent, with significant delays occurring sporadically. What is the most likely cause of these performance fluctuations?
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Question 4
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You are responsible for deploying an LLM in a customer service application. The LLM should effectively manage and prioritize different types of customer queries, such as urgent complaints, general inquiries, and feedback. However, during testing, you observe that the model struggles to prioritize urgent complaints appropriately, treating them with the same priority as general inquiries. The senior team member suggests adjusting the training process to improve the model's ability to handle priorities. Which strategy is most likely to improve the model’s ability to prioritize urgent complaints?
Answer: A
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You are responsible for deploying an LLM in a customer service application. The LLM should effectively manage and prioritize different types of customer queries, such as urgent complaints, general inquiries, and feedback. However, during testing, you observe that the model struggles to prioritize urgent complaints appropriately, treating them with the same priority as general inquiries. The senior team member suggests adjusting the training process to improve the model's ability to handle priorities. Which strategy is most likely to improve the model’s ability to prioritize urgent complaints?
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Question 5
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You have trained two different generative AI models, Model X and Model Y, on the same dataset. To compare their performance, you calculate the Mean Squared Error (MSE) and the proportion of explained variance (R²). Model X has a lower MSE but also a lower R² compared to Model Y. Which model is likely better at explaining the variability in the data?
Answer: C
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You have trained two different generative AI models, Model X and Model Y, on the same dataset. To compare their performance, you calculate the Mean Squared Error (MSE) and the proportion of explained variance (R²). Model X has a lower MSE but also a lower R² compared to Model Y. Which model is likely better at explaining the variability in the data?