Framework

PyTorch and TensorFlow are two widely used frameworks in the field of deep learning.

PyTorch, a product of Facebook’s AI Research lab (FAIR), has attracted many researchers and developers with features such as high compatibility with Python, ease of use, and providing advanced capabilities for building neural networks.

TensorFlow, developed by the Google Brain team, is one of the most popular frameworks in the field of machine learning. This framework, with features such as support for distributed computations, a variety of tools for visualization, and the ability to use different hardware such as GPUs and TPUs, has maintained its place among users.

The NVIDIA TAO Toolkit is an open-source software that simplifies and accelerates the creation of customized and enterprise-ready AI models for computer vision applications. It uses transfer learning, vision transformers, AutoML, and cloud-native technology to deliver high accuracy and performance on any platform1.

The Triton Inference Server (formerly known as TensorRT Inference Server or Triton) is a server software that standardizes the deployment and execution of AI models across every workload. The server supports trained AI models from many frameworks, including TensorFlow, TensorRT, PyTorch, and ONNX2.