PyTorch

This is your final opportunity to submit a session for #PyTorchDayChina taking place in Beijing on December 12. Bring your ideas and experiences to a community of PyTorch developers, machine learning engineers, AI researchers, and open source AI leaders from across China and beyond.

⏰ SUBMIT YOUR PROPOSAL by Tuesday, November 10, at 23:59 China Standard Time >> bit.ly/4imIAvV

"One thing that's special about the PyTorch Conference is that it really does focus on cutting-edge research and tools and trends that we see in AI."

Jana van Greunen, Director of Engineering, @Meta

At PyTorch Conference North America, our community gathered in person to accelerate open intelligence across the entire loop. From keynotes to technical deep dives, researchers, maintainers, and engineers came together to solve open bottlenecks and decide what comes next.

Read the full event recap: bit.ly/481GKe8

Catch the community highlights and hear directly from attendees: bit.ly/4zGi2vR

PyTorch Foundation, @CloudNativeFdn, and the @AgenticAIFdn are hosting an evening reception alongside NeurIPS in Sydney on December 8.

Meet researchers, engineers, and open source practitioners working across AI and cloud native infrastructure, and swap ideas over drinks and small bites.

The reception runs from 6 to 9 PM Sydney time on Tuesday, December 8, at Darling Pavilion, 1 Harbour St. Space is limited.

Find event details and registration at pytorch.org/event/cncf-pyt…

PyTorch operations can be performance optimized for MoE models applications.

MoE models replace a single dense feed-forward block with multiple expert networks. A naive implementation, however, can trigger excessive kernel launches. For example, the Hugging Face baseline implementation iterates over all experts in a Python loop, with each expert triggering separate kernel launches.

Grouped execution preserves the individual expert matrices but submits their work together, reducing launch and scheduling overhead. This blog from @nvidia uses biological foundation models as an example for efficient MoE training.

Read the full post:
bit.ly/4z2ulkW

Submit your proposal for PyTorch Day China 2026 before Tuesday, November 10, at 23:59 China Standard Time.

Propose a session presentation or lightning talk on model training and post-training, efficient inference and deployment, PyTorch Core and hardware acceleration, Physical AI, or PyTorch ecosystem tools and applications.

Share your work with PyTorch developers, machine learning engineers, AI researchers, and open source AI leaders in Beijing on December 12.

Read more: pytorch.org/blog/call-for-…