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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. What is a common method to reduce the computational cost of deep learning models during inference?

A) Adding more convolutional filters.
B) Increasing the batch size.
C) Pruning weights or neurons.
D) By replacing activation functions in some neurons with simpler ones.

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

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

3. 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) Applying multiple layers of kernels to improve model accuracy.
C) Optimizing model inference by reducing the number of computations by pruning.
D) Using kernel functions to optimize model hyperparameters.

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

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

5. During the process of data cleansing, which of the following steps is NOT typically performed?

A) Identifying and handling missing values
B) Transforming data into a different format
C) Removing duplicates
D) Collecting additional data

Solutions: