Question

A media streaming company wants to deploy a computer vision model for real-time content moderation on NVIDIA GPUs. Their MLOps team needs to reduce inference latency without retraining the model, and they want to start from a vendor-optimized, GPU-tuned build rather than compiling everything themselves. Which NVIDIA software resource is the most appropriate starting point?

Accepted Answer

Pull a TensorRT-optimized container and pretrained model from the NGC catalog

Answer

Install the standalone CUDA Toolkit and write custom kernels for the inference pipeline

Answer

Use cuDNN directly to hand-tune each convolution layer of the model

Answer

Rebuild the model in an unaccelerated CPU-only framework to simplify deployment