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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Trustworthy AI | 5% | - Ensuring fairness and transparency - Ethical considerations in AI development |
| Core ML & AI Knowledge | 20% | - Key algorithms and techniques - Basic concepts and terminology |
| Data Analysis & Visualization | 10% | - Data preprocessing and feature engineering - Visualization techniques for multimodal data |
| Software Development & Engineering | 15% | - Python libraries for multimodal AI - Integration and deployment of multimodal AI systems |
| Experimentation | 25% | - Experimental design - Model evaluation and comparison - A/B testing - Hypothesis testing |
| Performance Optimization | 10% | - Techniques for optimizing AI performance - Monitoring and improving system efficiency |
| Multimodal Data | 15% | - Applications and use cases - Handling and integrating text, image, and audio data |
NVIDIA Generative AI Multimodal Sample Questions:
1. What does 'kernel fusion' refer to in the context of AI model optimization?
A) Applying multiple layers of kernels to improve model accuracy.
B) Using kernel functions to optimize model hyperparameters.
C) Optimizing model inference by reducing the number of computations by pruning.
D) Combining multiple kernels into a single kernel for faster computation.
2. What is the purpose of a kernel in a Convolutional Neural Network (CNN)?
A) To classify the data into different categories.
B) To calculate the loss function.
C) To normalize the input data.
D) To perform convolution operations on input data.
3. How does CLIP understand the content of both text and images?
A) Through a database of predefined images with their descriptions.
B) By translating images into text and comparing them with the prompt.
C) Using contrastive learning to match images with text descriptions.
D) By converting text and images into a frequency domain for comparison.
4. What is a main application of Triton Inference Server?
A) Triton Server can be used to generate images from pure noise.
B) Triton Server can be used to deploy AI models on the GPU only.
C) Triton Server can be used to execute GPU-accelerated graph analysis with cuGraph.
D) Triton Server can be used to deploy neural networks from various frameworks.
5. Which technique is commonly used to speed up AI model training and inference on hardware accelerators?
A) Model enlargement
B) Data augmentation
C) Quantization
D) Dropout
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: C |
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