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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. What is the significance of A/B testing in ML software engineering?

A) A/B testing helps in optimizing the hyperparameters of a machine learning model.
B) A/B testing is used to measure the impact of changes in the user interface of a ML application.
C) A/B testing helps in evaluating the performance and effectiveness of different machine learning models.
D) A/B testing is irrelevant in ML software engineering.

2. What does 'kernel fusion' refer to in the context of AI model optimization?

A) Combining multiple kernels into a single kernel for faster computation.
B) Using kernel functions to optimize model hyperparameters.
C) Applying multiple layers of kernels to improve model accuracy.
D) Optimizing model inference by reducing the number of computations by pruning.

3. What is a main application of Triton Inference Server?

A) Triton Server can be used to generate images from pure noise.
B) Triton Server can be used to execute GPU-accelerated graph analysis with cuGraph.
C) Triton Server can be used to deploy neural networks from various frameworks.
D) Triton Server can be used to deploy AI models on the GPU only.

4. What is the purpose of a kernel in a Convolutional Neural Network (CNN)?

A) To calculate the loss function.
B) To classify the data into different categories.
C) To perform convolution operations on input data.
D) To normalize the input data.

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

Solutions: