PyTorch offers insights into deep learning, neural network modeling, and machine learning research, providing documentation, tutorials, and best practices for building and training models with PyTorch framework. By exploring PyTorch's curated content, developers can learn about tensor computations, autograd mechanisms, and model deployment strategies for solving complex problems in computer vision, natural language processing, and reinforcement learning. Whether you're a researcher, practitioner, or enthusiast, PyTorch offers resources to advance your understanding of deep learning and push the boundaries of AI innovation.

PyTorch

PyTorch Foundation expanded into an umbrella foundation in 2025, welcoming vLLM, DeepSpeed, and Ray as foundation-hosted projects alongside PyTorch. The foundation released four PyTorch versions (2.6-2.9), added 14 ecosystem projects and 16 new members including Snowflake and Qualcomm, and hosted the largest PyTorch Conference with 3,400+ attendees. For 2026, plans include three PyTorch Conferences (EU in Paris, China in Beijing, and flagship in San Jose), three PyTorch Days, new Associate and Professional certifications, expanded academic outreach, and focus on reinforcement learning and agentic AI systems under neutral governance.

PyTorch Foundation in 2025: A Year in Review and the Road Ahead – PyTorch

PyTorch Foundation Expansion and Foundation-hosted Projects

Ecosystem Growth and Working Group Updates