PyTorch is an open-source machine learning framework developed by Facebook's AI Research lab (FAIR), designed for flexibility and speed in building deep learning models. It has become a popular choice among researchers and developers for creating AI-driven solutions due to its dynamic computation graph and ease of use.

Features of PyTorch:

• Dynamic computation graph, allowing on-the-fly changes to the network structure for flexibility and debugging.
• Support for seamless integration with Python, making it intuitive and easy to learn.
• Comprehensive tools for deploying models to production, including mobile and cloud platforms.
• Rich ecosystem with libraries like TorchVision, TorchText, and TorchAudio for handling various data types.
• Built-in support for distributed training to scale models across multiple GPUs or nodes efficiently.
• A strong and growing community contributing tutorials, resources, and extensions to enhance the PyTorch ecosystem.

Disclaimer: PyTorch® is an open-source project maintained by the PyTorch development team and distributed under the BSD License. It is not affiliated with, endorsed by, or sponsored by any other entity. PyTorch is provided "as is," without any warranty, express or implied. Users are responsible for understanding and complying with licensing terms and regulations while using PyTorch.