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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

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

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

Question 2

Which of the following best describes the role of the Hugging Face model repository in ML software development?

A. A library for customizing large language models like GPT, LLaMA-2, and Falcon using the NeMo framework.
B. A set of NVIDIA SDKs, such as Riva, NeMo, Triton, and ACE, for implementing neural network architectures.
C. A platform for sharing and accessing pre-trained models and transformers for natural language processing.
D. A convenient tool for deploying neural networks for production-scale inference similar to Triton Server.

Question 3

In a Generative Adversarial Network (GAN), what is the role of the discriminator?

A. To optimize the training process.
B. To distinguish between real and generated data.
C. To calculate the loss function and update the generator.
D. To generate new data based on the training set.

Question 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. Line chart
B. Pie chart
C. Bar chart
D. Scatter plot

Question 5

What characteristic of autoencoders makes them suitable for anomaly detection?

A. Their ability to classify images with high accuracy.
B. Their capacity to learn a compressed representation of the data.
C. Their capability to predict future outcomes based on past data.
D. Their function in enhancing the quality of images.

Solutions: