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.

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The PyTorch Foundation has opened the Call for Proposals (CFP) for PyTorch Conference North America 2026, taking place October 20–21 in San Jose, California. Submissions are being accepted across six technical tracks: Applications, Training, Inference, Core PyTorch, Kernel Engineering, and Responsible AI, with a focus on PyTorch Foundation projects including PyTorch, vLLM, DeepSpeed, and Ray. The CFP closes June 7, with speaker notifications going out July 20. Super Early Bird registration is available until April 10, and sponsorship opportunities are open with Google, Arm, and Red Hat already signed on as Diamond/Platinum supporters.

Call for Proposals Open for PyTorch Conference North America 2026 – PyTorch

Technical Tracks and Submission Categories

Registration and Super Early Bird Savings