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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

What is contrastive learning in the context of multimodal deep learning? Pick the 2 correct responses below.

A. Contrastive learning is a technique used to train deep learning models by comparing similar and dissimilar inputs and optimizing the model to maximize the similarity between representations of similar inputs and minimize the similarity between representations of dissimilar inputs.
B. Contrastive learning is a technique used to manipulate and analyze multimodal data using Generative AI.
C. In a multimodal context, usually, contrastive learning decreases the similarity of representations across modalities for the same objects and increases the similarity of representations across modalities for different objects.
D. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the same objects and decreases the similarity of representations across modalities for different objects.
E. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the different objects and decreases the similarity of representations across modalities for same objects.

Question 2

Which of the following tasks can be performed using the transformer LLM encoder model?

A. Semantic analysis
B. Image generation
C. Speech recognition
D. Generating code

Question 3

Assume you need to implement a multimodal pipeline to diagnose brain cancer type using MRI scans and their corresponding radiology reports. What do you need to include in the ablation study?

A. Training a deep learning model using the images in the dataset to find outliers and enhancing the quality of MRI scans using image processing techniques.
B. More advanced natural language processing techniques to interpret radiology reports, ignoring the MRI scans' diagnostic value.
C. Implementing separate unimodal pipelines for each modality to ensure the data is informative and the model design is accurate.
D. Directly combining MRI scans and radiology reports into a single input stream without preprocessing or modality-specific adjustments.

Question 4

What is the role of CLIP (Contrastive Language-Image Pretraining) in text-to-image generation?

A. CLIP is used to generate image captions from textual input.
B. CLIP is used to enhance datasets through data augmentation for text-to-image generation.
C. CLIP provides a common embedding space for both the textual and image modalities.
D. CLIP is used to convert textual input into image embeddings.

Question 5

You are developing a GenAI-Multimodal system that uses data from various sources. What is one potential issue you need to consider in relation to bias in data?

A. The data used to train the AI system may not be representative of the population it is intended to serve.
B. Bias in data can only be addressed after the AI system has been deployed.
C. Bias in data is irrelevant as long as the AI system produces accurate predictions.
D. Bias in data is not a concern for AI systems as they are designed to be neutral and objective.

Solutions: