PyTorch Conference 2025

PyTorch Technical Deep Dive

Alban Desmaison, Peng Wu, Mark Saroufim & Edward Yang, Meta

PyTorch-Native Stack for Agents

Allen Wang & Davide Testuggine, Meta

Ray: A Distributed Compute Engine for AI

Robert Nishihara & Ion Stoica

Recognizing the PyTorch Foundation CICD Infrastructure Community

Eli Uriegas

Rethinking the Transformer: Toward Native Multimodal Architectures

Bowen Peng, Nous Research

Robot Foundation Models

Sergey Levine

Scaling Inference of O(10K)-length Sequence Recommendation Models Using...

S. Joshi & K. Rajesh

Scaling KV Caches for LLMs: How LMCache + NIXL Handle Network and Storage...- J. Jiang & M. Khazraee

Serving PyTorch LLMs at Scale: Disaggregated Inference With Kubernetes and Llm-d

M. Ayoub & C. Liu

SPDX: Tackling System Risk in Modern Supply Chains

Kate Stewart & Gary O'Neall

Sponsor Build AI Anywhere with ROCm™ Software: AMD and PyTorch Bring...

Anush Elangovan

Sponsor Session: Low-Precision Inference without Quality Loss...

Pankaj Gupta & Philip Kiely

Sponsored From Transactions to Transformers: Hardware Built for...

Christian Jacobi

Sponsored Unlocking AI at Scale for PyTorch Developers

Jeff Gehlhaar

The Building Blocks of Agentic Al

Joe Spisak, Product Director, Meta Superintelligence Labs

The Building Blocks of Today’s and Tomorrow’s Language Models

Sebastian Raschka, RAIR Lab

The Future Is Tiled: Using CuTile & TileIR To Write Portable, High-performance GPU...- Jared Roesch

The OpenMDW License Agreement: Simple, Permissive Terms for AI Model Materials

Steve Winslow

The Physical Turing Test: Solving General Purpose Robotics

Jim Fan, NVIDIA

Thunder: Distribute and Optimize Your PyTorch Models With Zero...

Luca Antiga & Thomas Viehmann

Towards Building Safe and Secure Agentic AI

Dawn Song, UC Berkeley

Transformers: Standardizing Model Definitions Across the PyTorch Ecosystem

L. Debut & A. Zucker

Unlock the Future of Generative AI: TorchTitan's Latest...

Tianyu Liu & Jiani Wang

Unlocking Performance: Harnessing LLMs To Streamline GPU Kernel Development in...

Jiannan Wang

Verl: A Flexible and Efficient RL Framework for LLMs

Hongpeng Guo & Ziheng Jiang, ByteDance Seed

vLLM & Deepspeed Updates

Simon Mo & Tunji Ruwase

Vllm-triton-backend: How To Get State-of-the-art Performance on...

B. Ringlein

vLLM: Easy, Fast, and Cheap LLM Serving for Everyone

Simon Mo, vLLM