NVIDIA NCA-GENM Practice Questions - NVIDIA-Certified Associate Multimodal Generative AI Exam - NVIDIA NCA-GENM Practice Questions - NVIDIA-Certified Associate Multimodal Generative AI Exam

Question 1

What does CLIP fundamentally learn during pretraining?

A joint embedding space where matched image-text pairs are close and unmatched pairs are far apart A pixel-level segmentation map of every image A token-by-token autoregressive model of captions only A frozen ResNet that is later fine-tuned on ImageNet

Correct Answer:

A joint embedding space where matched image-text pairs are close and unmatched pairs are far apart

Question 2

A Vision Transformer (ViT) processes an image by first doing what?

Splitting the image into fixed-size patches and projecting each patch into a token embedding Running a 50-layer convolutional backbone before any attention Converting the image to grayscale and applying FFT Tokenizing the image with BPE

Correct Answer:

Splitting the image into fixed-size patches and projecting each patch into a token embedding

Question 3

In a denoising diffusion probabilistic model (DDPM), what does the forward process do?

Gradually adds Gaussian noise to a clean sample over T steps following a fixed schedule Learns to remove noise with a U-Net Maps text prompts to image latents Performs classifier-free guidance

Correct Answer:

Gradually adds Gaussian noise to a clean sample over T steps following a fixed schedule

Question 4

Why does Stable Diffusion run the diffusion process in a latent space rather than directly on pixels?

Latent diffusion is dramatically cheaper in compute and memory than pixel-space diffusion at the same resolution Latent space removes the need for a text encoder It eliminates the need for any noise schedule It guarantees deterministic outputs

Correct Answer:

Latent diffusion is dramatically cheaper in compute and memory than pixel-space diffusion at the same resolution

Question 5

Classifier-free guidance (CFG) at inference time produces a sample by combining which two predictions?

The conditional noise prediction and the unconditional noise prediction, scaled by a guidance weight The forward and reverse diffusion steps Two independent diffusion checkpoints A discriminator score and a generator score

Correct Answer:

The conditional noise prediction and the unconditional noise prediction, scaled by a guidance weight

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About this Exam

Prepare with the NVIDIA NCA-GENM Practice Questions - NVIDIA-Certified Associate Multimodal Generative AI Exam practice quiz. This question bank includes 100 questions covering multimodal, model, models, prompt, and transformer. Use it to review important concepts, identify knowledge gaps, and build confidence for the related exam, course, or assessment.

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NVIDIA NCA-GENM Practice Questions - NVIDIA-Certified Associate Multimodal Generative AI Exam

This practice set contains 100 questions from the matching question bank and focuses on multimodal, model, models, prompt, and transformer. Work through each question carefully, review the provided solutions, and revisit topics that need more study before your next attempt.

This is an independent study resource intended for practice and review; it is not an official examination or an endorsement by any organization named in the title.

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NVIDIA NCA-GENM Practice Questions - NVIDIA-Certified Associate Multimodal Generative AI Exam

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