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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. How does the batch size influence VRAM consumption during inference with ML models on GPUs?

A) Decreasing the batch size reduces VRAM consumption.
B) Increasing or decreasing the batch size has the same impact on VRAM consumption.
C) Increasing the batch size reduces VRAM consumption because more data can be processed in parallel.
D) The batch size has no impact on VRAM consumption during inference.

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

3. How does CLIP understand the content of both text and images?

A) Using contrastive learning to match images with text descriptions.
B) By converting text and images into a frequency domain for comparison.
C) Through a database of predefined images with their descriptions.
D) By translating images into text and comparing them with the prompt.

4. You have a dataset containing information about sales performance for different regions in the last ten years.
Which type of data visualization would be most appropriate to compare the sales performance across regions on a year-by-year basis?

A) Line chart
B) Pie chart
C) Bar chart
D) Scatter plot

5. You are tasked with developing an image processing model using machine learning. You need to classify thousands of labeled images of cats and dogs. Which algorithm is commonly used for image classification?

A) Linear Regression
B) Decision Trees
C) Convolutional Neural Networks (CNN)
D) K-Means Clustering

Solutions: