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Guide for NVIDIA-Certified Associate: Multimodal Generative AI (NCA-GENM)

Quiz NVIDIA-Certified Associate: Multimodal Generative AI (NCA-GENM)

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Quiz

1/10
After fine-tuning a large language model (LLM) for generating legal documents, what is the most
effective way to assess whether the fine-tuning has improved the model’s performance for this specific
task?
Select the answer
1 correct answer
A.
Measuring the speed at which the fine-tuned model generates text, regardless of content accuracy.
B.
Evaluating the model’s output against a benchmark dataset of legal documents that it has never seen before.
C.
Comparing the fine-tuned model’s output with that of a non-fine-tuned model on random text generation tasks.
D.
Testing the fine-tuned model on a set of common, non-legal text generation tasks to measure general improvement.

Quiz

2/10
When customizing a Large Language Model (LLM) for a specific task, which approach is most efficient in
terms of computational resources and time while still ensuring high performance?
Select the answer
1 correct answer
A.
Using transfer learning by fine-tuning the top layers of the model on your domain-specific dataset.
B.
Retraining the entire model from scratch using your domain-specific dataset.
C.
Fine-tuning the model with only a few additional layers on a small dataset of examples.
D.
Customizing the model by manually editing its parameters based on trial and error.

Quiz

3/10
You are building a generative AI model that needs to create personalized marketing content based on
user data, including demographics, past purchases, and browsing history. Which data preprocessing
steps would most likely improve the quality and relevance of the generated content?
Select the answer
1 correct answer
A.
Applying PCA (Principal Component Analysis) to reduce the dimensionality of categorical variables.
B.
Scaling all numerical data to a range of 0-255 to mimic image preprocessing.
C.
Normalizing all numerical data and one-hot encoding categorical variables.
D.
Dropping all categorical variables and focusing only on numerical data.

Quiz

4/10
You are working with a multimodal generative AI model that processes both text and images to generate
detailed descriptions of objects. The model consistently produces inaccurate descriptions when
processing high-resolution images with complex backgrounds. Which two actions should you consider to
improve the model's performance in handling high-resolution images with complex backgrounds? (Select
two)
Select the answer
2 correct answers
A.
Use grayscale images instead of colored images.
B.
Reduce the image resolution before feeding it into the model.
C.
Increase the model’s learning rate to improve accuracy during training.
D.
Fine-tune the model using a pre-trained model specialized in object detection.
E.
Implement data augmentation techniques to diversify the training set with various background complexities.

Quiz

5/10
The AI development team has deployed a multimodal AI application that generates automated reports
from various data sources. After several weeks in production, users report that the application
occasionally generates incomplete reports, especially during times of high server usage. What is the
most effective strategy to identify and resolve this issue?
Select the answer
1 correct answer
A.
Conduct a thorough performance profiling and stress testing to identify bottlenecks
B.
Limit the application’s usage during peak hours to prevent overloading
C.
Reduce the complexity of the generated reports to decrease processing time
D.
Add more redundancy to the server infrastructure to handle the load

Quiz

6/10
You are tasked with developing a multimodal AI system that assists in medical diagnosis by analyzing
images, text reports, and patient history. To validate the effectiveness of your system, you conduct an
experiment where different prompt formulations are used to guide the model's diagnostic
recommendations. What is the most important aspect to consider when evaluating the effectiveness of
different prompts during experimentation?
Select the answer
1 correct answer
A.
The length of the prompts
B.
Accuracy of the model's diagnostic outputs
C.
The variety of medical cases tested
D.
The complexity of the prompts

Quiz

7/10
Which of the following is an example of a real-world application of generative AI in the creative industry?
Select the answer
1 correct answer
A.
Predicting customer behavior based on past purchase history.
B.
Filtering spam emails from legitimate ones in an email inbox.
C.
Generating realistic deepfake videos for entertainment and media purposes.
D.
Optimizing supply chain logistics using past data and AI models.

Quiz

8/10
You are working with a multimodal dataset that includes audio, video, and textual data for a sentiment
analysis project. During data preprocessing, you notice that the timestamps in the video files do not align
with the corresponding audio files, leading to inconsistencies. What is the most effective way to resolve
this issue before training your model?
Select the answer
1 correct answer
A.
Discard the audio data to simplify the model and avoid inconsistency issues.
B.
Normalize the data independently for each modality without adjusting the timestamps.
C.
Manually adjust the timestamps of each modality to ensure they align perfectly.
D.
Use a multimodal synchronization algorithm to automatically align the audio and video data.

Quiz

9/10
You are assisting in the development of a multimodal AI system that processes video data and related
textual captions to generate video summaries. Under the guidance of a senior team member, you wrote
a script that processes the video frames and aligns them with the corresponding captions. After
deploying your script, the senior member notices that the video summaries are not accurately
representing the content, and the alignment between video and text is inconsistent. What is the most
likely mistake in your script?
Select the answer
1 correct answer
A.
The script processes the text captions before extracting video frames, leading to a mismatch in data sequence.
B.
The script does not account for variations in the frame rate of the videos.
C.
The video frames were extracted at a fixed interval without considering scene changes.
D.
The script uses a standard tokenizer for text processing instead of a custom one.

Quiz

10/10
A content creation company is using a multimodal AI system to generate blog posts that include both text
and images. The AI system is supposed to generate relevant images that align closely with the text
content. However, the images generated often do not match the theme or context of the text, leading to a
disjointed user experience. Which prompt engineering strategy is most likely to improve the alignment
between the generated images and the text content?
Select the answer
1 correct answer
A.
Using a very short prompt to allow the AI system more creative freedom in generating images.
B.
Including specific details from the text content in the prompt for image generation.
C.
Using a prompt that describes the desired image in very general terms.
D.
Asking the model to generate images based on its interpretation of the text, without further guidance.
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Info quiz:

  • Quiz name:NVIDIA-Certified Associate: Multimodal Generative AI (NCA-GENM)
  • Total number of questions:420
  • Number of questions for the test:50
  • Pass score:80%

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