Browse Lessons

Sponsor Keynote: Build AI Anywhere with ROCm™ Software: AMD and PyTorch Bring... - Anush Elangovan

Keynote: PyTorch Technical Deep Dive - Alban Desmaison, Peng Wu, Mark Saroufim & Edward Yang, Meta

Keynote: Towards Building Safe and Secure Agentic AI - Dawn Song, UC Berkeley

Keynote: The Physical Turing Test: Solving General Purpose Robotics - Jim Fan, NVIDIA

Sponsored Keynote: Unlocking AI at Scale for PyTorch Developers - Jeff Gehlhaar

The Building Blocks of Today’s and Tomorrow’s Language Models - Sebastian Raschka, RAIR Lab

Lightning Talk: Challenges and Standardization in PyTorch Ecosystem... - Zesheng Zong & Ashok Emani

Keynote Panel: Hardwares & Accelerators - D Patel, S Zhou, P Salanki, N Perumbeti, M Saroufim

The Building Blocks of Agentic Al - Joe Spisak, Product Director, Meta Superintelligence Labs

Keynote: Welcome & Opening Remarks - Matt White, Executive Director, PyTorch Foundation

Keynote: Marin: An Open Lab for Frontier AI - Percy Liang, Together

Keynote: Ray: A Distributed Compute Engine for AI - Robert Nishihara & Ion Stoica

Keynote: An OPEN Path to Super Intelligence - Eric Xing

Keynote Panel Discussion: Signal vs. Noise: Betting on AI’s Next Wave

Keynote: vLLM & Deepspeed Updates - Simon Mo & Tunji Ruwase

Keynote Panel Discussion: Agentic AI - A. Dhinakaran, J. Liu, A. Jones, S. Colvin & B. Lorica

Keynote: Closing Remarks - Matt White, Executive Director, PyTorch Foundation

PyTorch APIs for High Performance MoE Training and Inference - D. Vega-Myhre; Ke Wen & N. Gimelshein

Sponsored Session: Lightning Talk: Improving Drug Discovery with Machine Learning... - Simon Axelrod

Bridging the Gap: Embedded Deployment of PyTorch Deep Learning Models in Complex Engineered Systems

Lightning Talk: What's New in Torch.onnx - Maanav Dalal & Justin Chu, Microsoft

Lightning Talk: Accelerating PyTorch FSDP Via Overlapping Collectives With In... - Nariaki Tateiwa

Deploying GenAI for Audio Generation on Mobile CPUs With ExecuTorch - Gian Marco Iodice, Arm

Sponsored Session: Beyond the Node: Scaling Inference with Cluster-Wide KVCache... - Alon Yariv

Leveraging PyTorch for Generative AI in Distributed Edge Clouds - Tina Tsou

Sponsored Session: Empowering AI Everywhere: Democratizing PyTorch with Intel... - F. Zhao & E. Wang

DeepSpeed: Efficient Training Scalability for Deep Learning - Tunji Ruwase, Snowflake

Lightning Talk: Unlock the Future of Generative AI: TorchTitan's Latest... - Tianyu Liu & Jiani Wang

Sponsored Session: Arctic Inference: Breaking the Speed-Cost Tradeoff in LLM Serving - Aurick Qiao

Sponsored Session: Distributed Training in PyTorch: Zero to Hero - Corey Lowman, Lambda Labs

Efficient MoE Pre-training at Scale on AMD GPUs With TorchTitan -Liz Li & Yanyuan Qin, Matthias Reso

Sponsored Session: Lightning Talk: PyTorch in Production: Boosting LLM Training and... - F. Hua

Enabling VLLM V1 on AMD GPUs With Triton - Thomas Parnell, IBM Research & Aleksandr Malyshev, AMD

Multi-Accelerator PyTorch Serving With NxD Inference and vLLM - Yahav Biran & Liangfu Chen, Amazon

Lightning Talk: Improved GEMM and SDPA Performance on ROCm With Composable Kernel - Andres Lugo, AMD

Sponsored Session: Lightning Talk: Per-iteration PyTorch Visibility... - Shruti Verma & Yi-Ting Wu

Blazing Fast GenAI Inference With Torch.compile - Richard Zou, Meta

PyTorch Symmetric Memory: A New Programming Paradigm for Distributed AI - Ke Wen & Chien-Chin Huang

Lightning Talk: Vllm-triton-backend: How To Get State-of-the-art Performance on... - B. Ringlein

Sponsored Session: Lightning Talk: PyTorch and Democratization of AI Accelerators - Hong-Seok Kim

Sponsor Session: Low-Precision Inference without Quality Loss... - Pankaj Gupta & Philip Kiely

Sponsored Session: PyTorch Distributed and Fault Tolerance - Tristan Rice, Meta

Transformers: Standardizing Model Definitions Across the PyTorch Ecosystem - L. Debut & A. Zucker

Helion: A High-level DSL for Kernel Authoring - Jason Ansel, Meta

Enabling Lightweight, High-Performance FSDP With NVIDIA GPU - J. Chang CN, C. Ye, X. Chen & S. Lym

Verl: A Flexible and Efficient RL Framework for LLMs - Hongpeng Guo & Ziheng Jiang, ByteDance Seed

Lightning Talk: In-Cluster Distributed Checkpointing: Optimizing Training... - G. Kroiz & S. Mishra

Lightning Talk: FTorch: A Library To Couple PyTorch ML Models With Fortran Climate Models - M Archer