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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. In large-language models, what is the purpose of the attention mechanism?

A) To measure the importance of the words in the output sequence.
B) To determine the order in which words are generated.
C) To assign weights to each word in the input sequence.
D) To capture the order of the words in the input sequence.

2. How does the batch size influence VRAM consumption during inference with ML models on GPUs?

A) Increasing the batch size reduces VRAM consumption because more data can be processed in parallel.
B) Increasing or decreasing the batch size has the same impact on VRAM consumption.
C) The batch size has no impact on VRAM consumption during inference.
D) Decreasing the batch size reduces VRAM consumption.

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

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

4. Which technique is commonly used to speed up AI model training and inference on hardware accelerators?

A) Data augmentation
B) Dropout
C) Quantization
D) Model enlargement

5. Which technique involves leveraging pre-trained models to achieve efficient results with less data and computation?

A) Transfer learning
B) Neural network integration
C) State management and composition
D) Prompt engineering

Solutions: