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

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

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

3. What does mixed-precision training refer to?

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

4. What role does 'late fusion' play in multimodal machine learning?

A) It refers to the process of combining multiple modalities at the training stage.
B) It refers to the process of combining multiple modalities at the decision level.
C) It refers to the process of combining multiple modalities at the feature level.
D) It refers to the process of combining multiple modalities at the preprocessing stage.

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

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

Solutions: