Free Practice Dell EMC NCA-GENM Exam Questions 2025

Stay ahead with 100% Free NCA - Generative AI Multimodal NCA-GENM Dumps Practice Questions

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Total 420 Questions | Updated On: Jan 28, 2025

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Question 1

After fine-tuning a large language model (LLM) for generating legal documents, what is the most effective way to assess whether the fine-tuning has improved the model’s performance for this specific task?

A : Comparing the fine-tuned model’s output with that of a non-fine-tuned model on random text generation tasks.

B : Testing the fine-tuned model on a set of common, non-legal text generation tasks to measure general improvement.

C : Evaluating the model’s output against a benchmark dataset of legal documents that it has never seen before.

D : Measuring the speed at which the fine-tuned model generates text, regardless of content accuracy.

Answer: C

Question 2

You are tasked with developing a Retrieval-Augmented Generation (RAG) system for a chatbot that helps users troubleshoot technical issues. The chatbot needs to understand queries about a wide range of topics and respond with accurate, contextually relevant information. Which approach would best improve the chatbot's performance in handling diverse queries?

A : Integrating a domain-specific knowledge graph with the RAG system

B : Using a hybrid retrieval model that combines both keyword-based search and semantic search

C : Implementing a multi-turn dialogue management system without retrieval

D : Fine-tuning a pre-trained LLM specifically on a technical support knowledge base

Answer: A

Question 3

In developing a generative AI system, how can you balance the need for data privacy with the importance of obtaining data consent to ensure the ethical use of personal information?

A : Prioritizing the AI system’s performance over user privacy concerns.

B : Ensuring that all data collection processes are transparent and that explicit consent is obtained from users before using their data.

C : Collecting as much data as possible without informing users to improve AI accuracy.

D : Using default settings that automatically opt users into data sharing without their explicit knowledge.

Answer: B

Question 4

You are tasked with developing a multimodal AI system for autonomous drones that perform search and rescue operations in remote areas. The system must integrate visual input from cameras with audio signals to locate and identify distressed individuals. Given the energy constraints and the need for real-time decision-making, which approach should you prioritize to optimize the system for both performance and energy efficiency?

A : Utilize a lightweight model architecture specifically designed for mobile and edge devices.

B : Increase the resolution of camera inputs to enhance image quality and accuracy.

C : Disable the audio processing component to reduce energy consumption.

D : Employ a more complex multimodal fusion strategy to improve the integration of audio and visual data.

Answer: A

Question 5

You need to deploy an end-to-end conversational AI pipeline on NVIDIA Riva that supports multiple languages. What is the most effective approach to ensure accurate ASR, NLP, and TTS performance across different languages?

A : Use a multilingual dataset for training the ASR model and apply it to NLP and TTS as well.

B : Fine-tune individual ASR, NLP, and TTS models for each language and deploy them in parallel.

C : Train a single model that can handle all languages for ASR, NLP, and TTS.

D : Deploy separate ASR models for each language but use a common NLP and TTS model.

Answer: B

Page: 1 / 84

Total 420 Questions | Updated On: Jan 28, 2025

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