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In his talk at PyTorch Conference North America, Maajid Khan from Fujitsu Research India will explore efficient MoE LLM ...

PyTorch strives to offer tested and proven optimizers (think SGD, AdamW, Muon) and we want them to be fast, consistent, and ...

AI computing has moved from chips to platforms, and now to ecosystems. Cambricon's decade-long journey has proven that scale ...

Accelerating Sequential Recommender Models in the PyTorch Ecosystem - Zan Huang & Jiayu Sun, NVIDIA Sequential ...

As AI models grow larger and their architectures become increasingly sophisticated, the industrial ecosystem faces new ...

In 2026, PyTorch stands at the center of a rapidly expanding global AI ecosystem. Through a data-driven analysis of activity ...

AI computing hardware faces severe heterogeneity challenges with high adaptation costs and lack of unified standards.

As AI hardware continues to diversify, PyTorch faces a growing challenge: many of its APIs, runtime interface, and test ...

No single project, company, or community builds the AI stack alone. Behind the models, frameworks, cloud native technologies, ...

The pace of AI innovation requires an open ecosystem where researchers, developers, model builders and hardware companies ...

Struggling to understand tensor dimensions and shapes in PyTorch? In this video, we visualize what every single bracket ...

How does the threshold activation function operate on multi-dimensional tensors in deep learning? In this video, we visualize ...

Struggling to visualize complex tensor slicing and indexing in PyTorch? In this video, we animate tensor extractions step by step: ...

Why is the square root operation essential in deep learning, standard deviation, and Transformer attention scaling? In this video ...

Notebook + trained model: https://buymeacoffee.com/general_kihara/e/561452 Full course on Udemy (Scikit-Learn + PyTorch + ...

How does computing the mean along specific axes alter multi-dimensional tensors in PyTorch? In this video, we visualize ...

Adapting to PyTorch's rapid bi-monthly release cycle is a challenge for heterogeneous accelerators. This session shares Ascend's ...

Chapter 10 of the Complete Machine Learning & Deep Learning Bootcamp: your first neural network in PyTorch 2.x — tensors ...

Nonlinearity and Activation Functions in PyTorch explained in a simple and beginner-friendly way. In this video, you will learn ...