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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. What does mixed-precision training refer to?

A) Training a model using diverse data types while addressing challenges related to missing or incomplete information.
B) Training a model using incomplete or missing information from different modalities.
C) Training a model using different types of data, such as text, images, audio, time series, and geospatial information.
D) Training a model using multiple precision levels, such as using both single-precision and double- precision floating-point numbers.

2. 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 increases the similarity of representations across modalities for the different objects and decreases the similarity of representations across modalities for same 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 same objects and decreases the similarity of representations across modalities for different objects.
E) 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.

3. In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?

A) Support vector machine (SVM)
B) K-means clustering
C) Decision tree
D) Generative adversarial network (GAN)

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

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

5. You have been given a dataset with missing values. What is the first step you should take with the data?

A) Fill in the missing values with a default value.
B) Remove the rows with missing values.
C) Remove the columns with missing values.
D) Analyze the patterns and distribution of missing values.

Solutions: