NCA-GENM Question 176
Select 2You are tasked with developing a generative AI system capable of creating high-quality, domain-specific images based on textual descriptions. The project scope includes implementing U-Net-based architectures, integrating a text-to-image model like CLIP, and refining the system with prompt engineering techniques. You also need to leverage NVIDIA SDKs to optimize AI performance and deployment. Which combination of NVIDIA SDKs would most effectively support this task?
- A
NVIDIA NeMo™ for pretraining and fine-tuning the language models used in prompt engineering
- B
NVIDIA Triton™ Inference Server for optimizing the deployment of the generative AI model
- C
NVIDIA Riva for real-time conversational AI integration with your image generation system
- D
NVIDIA Avatar Cloud Engine (ACE) for scaling interactive avatar-based experiences
- E
NVIDIA CUDA Toolkit for low-level GPU acceleration of the U-Net model
Show answer and explanation
Correct answers: A, B
Explanation
To build a generative AI system for text-to-image tasks, leveraging NVIDIA NeMo™ allows for advanced language model tuning and effective prompt engineering, while NVIDIA Triton™ optimizes the deployment and scaling of the model. Other options, such as Riva and ACE, are designed for different use cases, and CUDA Toolkit, while powerful, is a lower-level tool compared to the specialized SDKs mentioned.
- A. Correct.
NVIDIA NeMo™ is well-suited for tasks involving fine-tuning language models, making it essential for prompt engineering and optimizing the text-to-image generation process.
- B. Correct.
NVIDIA Triton™ Inference Server is designed for efficient AI model deployment, allowing for scalable and optimized inference of the generative model.
- C. Incorrect.
NVIDIA Riva is primarily focused on conversational AI tasks, which are not directly relevant to this specific use case of generative image creation.
- D. Incorrect.
NVIDIA Avatar Cloud Engine (ACE) is focused on creating interactive avatar technologies, which are not directly applicable to this system unless it involves avatar-related outputs.
- E. Incorrect.
While the NVIDIA CUDA Toolkit could be used for GPU acceleration, the question specifically focuses on higher-level SDKs tailored for generative AI tasks, making it less relevant in this context.