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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. Which of the following is a disadvantage of the ReLU activation function?

A) It can cause dead neurons.
B) It is prone to vanishing gradient problem.
C) It is computationally expensive.
D) It is not suitable for deep neural networks.

2. You want to evaluate the performance of an AI model. Which of the following is a method for AI model evaluation?

A) Calculating the loss function of the model on the training set.
B) Calculating the model's accuracy from randomly selected data points from the dataset not used during the model's training.
C) Interviewing the developers of the AI model to assess its performance.
D) Randomly selecting data points from the training set and calculating the accuracy of the model on these data points.

3. In convolutional neural networks, we may use padding in both convolution and transposed convolution.
Which two (2) statements accurately describe padding in convolution and transposed convolution? Pick the 2 correct responses below.

A) Padding in convolution enables convolution operations on the boundary pixels of the input. In transposed convolution, it removes rows and columns along the perimeter of the input after it is expanded with stride.
B) In a convolution operation, padding is added to the output after it has been expanded with the stride. On the other hand, in a transposed convolution operation, padding is added to the input before it is expanded with stride.
C) Padding in convolution is used only when the input image is smaller than the filter size, while padding in transposed convolution is used only when the input image is larger than the filter size.
D) Padding in convolution increases the spatial dimensions of the input feature map, while padding in transposed convolution decreases the spatial dimensions of the output feature maps.
E) Padding in convolution and transposed convolution serve the same purpose of reducing the convolutional neural network's memory requirement and computational cost of the convolutional neural network.

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) Scatter plot
C) Bar chart
D) Pie chart

5. 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 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.

Solutions: