Leading businesses across industries are beginning to use PyTorch to both facilitate their research and then also deploy at large scale for applications such as translation, computer vision, conversational interfaces, pharmaceutical research, factory optimization, and automated driving research. Community adoption of PyTorch has also continued to expand. Stanford, UC Berkeley, Caltech, and other universities are using PyTorch as a fundamental tool for their machine learning (ML) courses; new ecosystem projects have launched to support development on PyTorch; and major cloud platforms have expanded their integration with PyTorch.
Using PyTorch across industries
Many leading businesses are moving to PyTorch 1.0 to accelerate development and deployment of new AI systems. Here are some examples:

Airbnb leveraged PyTorch's rich libraries and APIs for conversational AI and deployed a Smart Reply to help the company’s service agents respond more effectively to customers.
