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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: NVIDIA AI Ecosystem | - NVIDIA tools and frameworks
|
| Topic 2: Responsible and Trustworthy AI | - Ethical AI principles - Bias and safety considerations |
| Topic 3: Generative AI Concepts | - Generative models
|
| Topic 4: Core AI and Machine Learning Fundamentals | - Machine learning basics
|
| Topic 5: Multimodal AI Systems | - Cross-modal learning
|
NVIDIA Generative AI Multimodal Sample Questions:
You are developing a GenAI-Multimodal system that uses data from various sources. What is one potential issue you need to consider in relation to bias in data?
- A. Bias in data is not a concern for AI systems as they are designed to be neutral and objective.
- B. Bias in data is irrelevant as long as the AI system produces accurate predictions.
- C. Bias in data can only be addressed after the AI system has been deployed.
- D. The data used to train the AI system may not be representative of the population it is intended to serve.
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Which of the following best describes the role of the Hugging Face model repository in ML software development?
- A. A set of NVIDIA SDKs, such as Riva, NeMo, Triton, and ACE, for implementing neural network architectures.
- B. A convenient tool for deploying neural networks for production-scale inference similar to Triton Server.
- C. A platform for sharing and accessing pre-trained models and transformers for natural language processing.
- D. A library for customizing large language models like GPT, LLaMA-2, and Falcon using the NeMo framework.
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In large-language models, what is the purpose of the attention mechanism?
- A. To measure the importance of the words in the output sequence.
- B. To determine the order in which words are generated.
- C. To assign weights to each word in the input sequence.
- D. To capture the order of the words in the input sequence.
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In a Generative Adversarial Network (GAN), what is the role of the discriminator?
- A. To optimize the training process.
- B. To generate new data based on the training set.
- C. To distinguish between real and generated data.
- D. To calculate the loss function and update the generator.
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In the development of Trustworthy AI, what is the significance of 'Certification' as a principle?
- A. It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
- B. It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
- C. It ensures that AI systems are transparent in their decision-making processes.
- D. It requires AI systems to be developed with an ethical consideration for societal impacts.
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