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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

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

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

2. What is the purpose of the cuDNN library?

A) To measure GPU usage and other metrics with Prometheus.
B) To optimize deep neural network computations on NVIDIA GPUs.
C) To generate images from English text-prompts using CLIP.
D) To implement GPU-accelerated data preparation and feature extraction.

3. In a multimodal machine learning context, how are different modalities usually linked to each other?

A) Different modalities are not linked to each other in a multimodal machine learning context.
B) Different modalities are linked through separate models that are ensembled by tree-based models.
C) Different modalities are linked through a shared representation that captures the relationships between the modalities.
D) Different modalities are linked through random connections.

4. In multimodal machine learning, what does 'early fusion' refer to?

A) Integrating different modalities at the beginning of the model pipeline.
B) Training separate models for each modality and then combining their predictions.
C) Ignoring certain modalities and only using one modality for analysis and prediction.
D) Implementing the model in the early stages of development of the ML solution.

5. What are some methods to overcome limited throughput between CPU and GPU?

A) Increase the clock speed of the CPU.
B) Using techniques like memory pooling.
C) Upgrade the GPU to a higher-end model.
D) Increase the number of CPU cores.

Solutions: