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In an AI environment, the NVIDIA software stack plays a crucial role in ensuring seamless operations across different stages of the AI workflow. Which components of the NVIDIA software stack would you use to accelerate AI model training and deployment? (Select two)
Correct Answer: A,B
For AI model training and deployment: * NVIDIA cuDNN(A) accelerates training by providing optimized GPU primitives (e.g., convolutions) for deep neural networks, used by frameworks like PyTorch and TensorFlow. * NVIDIA TensorRT(B) optimizes models for deployment, enhancing inference speed and efficiency on GPUs. * NVIDIA DGX-1(C) is hardware, not a software component. * NVIDIA Nsight(D) is for profiling, not direct acceleration of training/deployment. * NVIDIA DeepStream SDK(E) is for video analytics, not general AI workflows. cuDNN and TensorRT are core to NVIDIA's AI software stack (A and B).