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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. How does CLIP understand the content of both text and images?

A) By converting text and images into a frequency domain for comparison.
B) Using contrastive learning to match images with text descriptions.
C) By translating images into text and comparing them with the prompt.
D) Through a database of predefined images with their descriptions.

2. What does mixed-precision training refer to?

A) Training a model using multiple precision levels, such as using both single-precision and double- precision floating-point numbers.
B) Training a model using incomplete or missing information from different modalities.
C) Training a model using different types of data, such as text, images, audio, time series, and geospatial information.
D) Training a model using diverse data types while addressing challenges related to missing or incomplete information.

3. Which framework is used for conversational AI models development?

A) NVIDIA Metropolis
B) NVIDIA NeMo
C) NVIDIA DeepStream
D) NVIDIA Clara

4. Which metric is commonly used to evaluate machine-translation models?

A) BLEU score
B) Accuracy
C) F1 score
D) Mean Absolute Error (MAE)

5. In a multimodal machine learning context, how are different modalities usually linked to each other?

A) Different modalities are linked through a shared representation that captures the relationships between the modalities.
B) Different modalities are not linked to each other in a multimodal machine learning context.
C) Different modalities are linked through separate models that are ensembled by tree-based models.
D) Different modalities are linked through random connections.

Solutions: