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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. In the transformer architecture, what is the purpose of positional encoding?

A) To add information about the order of each token in the input sequence.
B) To encode the importance of each token in the input sequence.
C) To encode the semantic meaning of each token in the input sequence.
D) To remove redundant information from the input sequence.

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

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

3. For building a zero-shot image classification pipeline, what could be a crucial step in the process?

A) Using a model like CLIP for encoding both images and their textual descriptions into a shared representation space for comparison.
B) Focusing on enhancing the resolution and quality of images before classification.
C) Manually labeling each image in the dataset for precise classification.
D) Designing an algorithm to replace the need for textual descriptions in the classification process.

4. You have a dataset containing information about sales performance for different regions in the last ten years.
Which type of data visualization would be most appropriate to compare the sales performance across regions on a year-by-year basis?

A) Scatter plot
B) Line chart
C) Pie chart
D) Bar chart

5. Which of the following tasks can be performed using the transformer LLM encoder model?

A) Semantic analysis
B) Image generation
C) Speech recognition
D) Generating code

Solutions: