Technical Blog

Clinical applications for AI are improving digital surgery, helping to reduce errors, provide consistency, and enable surgeon augmentations that were previously... 4 MIN READ

Crafted by AI for AI, GPUNet is a class of convolutional neural networks designed to maximize the performance of NVIDIA GPUs using NVIDIA TensorRT. Built using... 6 MIN READ

If you’re an active Jetson developer, you know that one of the key benefits of NVIDIA Jetson is that it combines a CPU and GPU into a single module, giving... 3 MIN READ

Imagine that you have trained your model with PyTorch, TensorFlow, or the framework of your choice, are satisfied with its accuracy, and are considering... 11 MIN READ

The primary function of NVIDIA TensorRT is the acceleration of deep-learning inference, achieved by processing a network definition and converting it into an... 16 MIN READ

We’re excited to announce the NVIDIA Quantization-Aware Training (QAT) Toolkit for TensorFlow 2 with the goal of accelerating the quantized networks with... 9 MIN READ