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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

How is the optimization of a multimodal model different from a unimodal model in terms of gradient vanishing?

A. Both multimodal and unimodal models have an equal risk of gradient vanishing, as the optimization process is independent of the number of modalities.
B. Gradient vanishing is not a concern in either multimodal or unimodal models, as modern optimization techniques have overcome this issue.
C. Multimodal models have a higher risk of gradient vanishing compared to unimodal models, as the combination of multiple modalities increases the complexity of the model architecture.
D. Unimodal models have a higher risk of gradient vanishing compared to multimodal models, as the focus on a single modality allows for better gradient flow and stability.

Question 2

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

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

Question 3

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. Bar chart
B. Scatter plot
C. Pie chart
D. Line chart

Question 4

In the context of multimodal machine learning, what does 'data fusion' refer to?

A. Removing missing or incomplete information from different modalities.
B. Evaluating the quality of diverse data types in multimodal machine learning.
C. Combining different modalities of data into a single representation.
D. Separating different modalities of data into distinct representations.

Question 5

During the process of data cleansing, which of the following steps is NOT typically performed?

A. Transforming data into a different format
B. Collecting additional data
C. Removing duplicates
D. Identifying and handling missing values

Solutions: