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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. In LLM evaluation, what does "zero-shot learning" refer to?

A) The model's performance after extensive training
B) The model's ability to perform tasks it has not been explicitly trained on
C) A technique to reduce training time to zero
D) The model's ability to learn from zero examples

2. You are developing a ML model for image classification. You have a dataset with 10,000 images of cats, dogs and birds. Which of the following ML models would be the most appropriate choice for this task?

A) Convolutional Neural Network (CNN)
B) K-Means Clustering
C) Logistic Regression
D) Linear Regression

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

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

4. What is the role of CLIP (Contrastive Language-Image Pretraining) in text-to-image generation?

A) CLIP is used to enhance datasets through data augmentation for text-to-image generation.
B) CLIP is used to convert textual input into image embeddings.
C) CLIP is used to generate image captions from textual input.
D) CLIP provides a common embedding space for both the textual and image modalities.

5. In the context of multimodal machine learning, what does 'data fusion' refer to?

A) Separating different modalities of data into distinct representations.
B) Evaluating the quality of diverse data types in multimodal machine learning.
C) Removing missing or incomplete information from different modalities.
D) Combining different modalities of data into a single representation.

Solutions: