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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

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

A) 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.
B) Contrastive learning is a technique used to manipulate and analyze multimodal data using Generative AI.
C) 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.
D) 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.
E) 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.

2. For building a zero-shot image classification pipeline, what could be a crucial step in the process?

A) Using a model like CLIP for encoding both images and their textual descriptions into a shared representation space for comparison.
B) Manually labeling each image in the dataset for precise classification.
C) Focusing on enhancing the resolution and quality of images before classification.
D) Designing an algorithm to replace the need for textual descriptions in the classification process.

3. What role does 'late fusion' play in multimodal machine learning?

A) It refers to the process of combining multiple modalities at the feature level.
B) It refers to the process of combining multiple modalities at the preprocessing stage.
C) It refers to the process of combining multiple modalities at the decision level.
D) It refers to the process of combining multiple modalities at the training stage.

4. What is the purpose of the cuDNN library?

A) To measure GPU usage and other metrics with Prometheus.
B) To implement GPU-accelerated data preparation and feature extraction.
C) To generate images from English text-prompts using CLIP.
D) To optimize deep neural network computations on NVIDIA GPUs.

5. In large-language models, what is the purpose of the attention mechanism?

A) To determine the order in which words are generated.
B) To measure the importance of the words in the output sequence.
C) To assign weights to each word in the input sequence.
D) To capture the order of the words in the input sequence.

Solutions: