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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. Which metric is commonly used for evaluating Automatic Speech Recognition (ASR) models?

A) F1 Score
B) CTC Loss
C) Mean Opinion Score (MOS)
D) Word Error Rate (WER)

2. What is the significance of using a U-Net like architecture in denoising diffusion probabilistic models?

A) To generate new images from pure noise.
B) To classify input images as noisy or clean.
C) To detect noisy objects in input images.
D) To segment noisy patches in input images.

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

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

4. In the development of Trustworthy AI, what is the significance of 'Certification' as a principle?

A) It ensures that AI systems are transparent in their decision-making processes.
B) It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
C) It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
D) It requires AI systems to be developed with an ethical consideration for societal impacts.

5. What is the purpose of the cuDNN library?

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

Solutions: