Question 1

You are part of a team developing a multimodal AI system that recommends music videos based on users' preferences, which include both visual aesthetics and musical genres. The system’s success depends on how well the dataset is curated and labeled with both visual and audio features. What is the most important step when curating and labeling the dataset for this recommendation system?

Options :

A : Prioritizing high-definition video content

B : Using short clips to save on storage space

C : Selecting only popular music videos for the dataset

D : Ensuring that both visual and audio elements are accurately labeled

Answer: D

Question 2

When customizing an LLM for a specific industry task where quick deployment and computational efficiency are priorities, which of the following methods would be most appropriate?

Options :

A : Using the original LLM without any modifications to handle industry-specific tasks.

B : Fine-tuning an existing large model on a small, targeted dataset specific to the industry.

C : Training a new model from scratch using industry-specific data.

D : Applying data augmentation techniques on the industry-specific dataset without fine-tuning the model.

Answer: B

Question 3

You are experimenting with different AI model architectures for a multimodal project that integrates text, image, and audio data. One model architecture shows high accuracy on the training set but fails to generalize well to the validation set. What is the most appropriate next step to evaluate and improve this model?

Options :

A : Switch to a more complex model architecture with additional layers.

B : Increase the number of epochs to further train the model.

C : Reduce the size of the training set to decrease overfitting.

D : Use cross-validation to better evaluate the model’s generalization.

Answer: D

Question 4

Which of the following best describes the role of the denoising diffusion process in enhancing the quality of images generated by diffusion models?

Options :

A : The denoising diffusion process iteratively refines the image by reducing noise and enhancing details over multiple steps, leading to higher quality outputs.

B : The denoising diffusion process applies a single pass of noise reduction to the final image, enhancing sharpness and clarity.

C : The denoising diffusion process is used only at the beginning of image generation to set an initial low-noise state.

D : The denoising diffusion process relies on pre-generated noise patterns to create detailed images.

Answer: A

Question 5

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?

Options :

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

Higher Test Marks with Free Online NCA-GENM Exam Practice

Buying Options: