PyTorch

Validate your real-world PyTorch skills with the PyTorch Certified Associate (PTCA) program. Designed for early-stage practitioners, PTCA helps you demonstrate foundational ability across model design, training, and deployment while building credibility across the open source AI ecosystem. Learn more and enroll here: bit.ly/4do6qEx

We ❤️ our ambassadors. The ambassador meetup at #PyTorchCon North America was a good time to connect and make plans for the year ahead. PyTorch Foundation Ambassadors help grow our projects (PyTorch, vLLM, DeepSpeed, Ray, Helion, & Safetensors) around the world by organizing events, creating educational content, mentoring new users, and contributing to the open source ecosystem. Meet all of your PyTorch Foundation ambassadors: pytorch.org/programs/ambassa…

🚀 Unlock frontier-level AI training performance with DeepSpeed! bit.ly/4zLzUoS Join Masahiro Tanaka of DeepSpeed at PyTorch Day Japan 2026 as he presents “DeepSpeed at the Frontier: Community-Driven Optimizations for State-of-the-Art Training Performance,” exploring the latest innovations advancing the performance and scalability of distributed AI training. Register by November 11 and save ¥3,000. bit.ly/4zMCquV

PyTorch 2.15 is here, with 3,117 commits from 583 contributors and updates across distributed training, NVGEMM, Apple Silicon, and accelerator platform support. The release makes the rewritten NCCL backend the default and adds one-sided transports with a NIXL backend. FSDP2 and pipelining gain finer memory and communication control. It also brings faster 4-bit (NVFP4) LLM decoding on NVIDIA Blackwell GPUs, FP8 and faster decode on Apple Silicon, and broader platform support. On Thursday, November 5, at 11 AM PST, join Tristan Rice (@rice_fry), Natalia Gimelshein, Huy Do, and Jane Xu (@janeyx99) (@Meta) for a live PyTorch 2.15 Q&A, moderated by Chris Gottbrath (Gottbrath Tech). The speakers will share an overview of the release and answer community questions about PyTorch and the new capabilities in this release. 🔗 Read the release blog and register for the live Q&A: pytorch.org/blog/pytorch-2-1…

On Oct 19 at PyTorch Conference North America 2026 in San Jose, attendees spent a full day in our instructor-led PyTorch Associate Training preparing for the PyTorch Certified Associate (PTCA) exam. Here’s what they had to say: 💬 “From basics to advanced, the instructors did a nice job of explaining.” 💬 “Everything was hands-on... with powerful GPUs.” 💬 “I used to think of PyTorch as training models, but it was so much more: benchmarking and profiling.” 💬 “Made me confident for the exam.” 💬 “Absolutely recommend to friends.” Thank you to our teaching staff from @NVIDIAAI: Allison Ding, Krishna Kalyan, Lakshay Garg, Santosh Bahir, Ian Wang, and Faradawn Yang. Learn more about getting certified: bit.ly/4do6qEx Check out what the attendees had to say here: bit.ly/4Bvhb2j #PyTorchCon

Faster streaming speech recognition on @Arm edge devices: see how ExecuTorch, SME2, FP16 and QC8W balance accuracy and latency—delivering up to 2.12× faster processing on Pixel 11. Read our latest blog: pytorch.org/blog/optimizing-… ✍ Josiah Davis, Kshitij Sisodia

Smaller & specialized models are becoming dramatically more capable and new approaches to continual learning are enabling AI systems to improve from real-world experience after deployment. Jonathan Bryce, Executive Director of Cloud & Infrastructure at @linuxfoundation @CloudNativeFdn shares about how we're moving from bigger models to better systems during @AgenticAIFdn #AGNTCon + #MCPCon keynote. The future of AI will depend not on any single model, but on an open set of technologies for building, optimizing, serving and continuously improving intelligence. The @PyTorch Foundation in bringing those technologies together, creating an open foundation that gives developers the freedom to build with any model, on any chip and across any cloud.

#PyTorchCon North America 2026 brought 3,500+ attendees to San Jose to accelerate open intelligence. The PyTorch Foundation welcomed nine new members, including @Nebius, @Nscale, and @Shopify as Platinum members, deepening its role as the intelligence layer for open source AI development. “Open systems learn faster when more people, projects, and organizations are working together, creating compounding gains,” said @sparkycollier, Executive Director of the PyTorch Foundation. “Open source ecosystems let breakthroughs travel between organizations instead of staying locked inside one company.” @Google and @Meta introduced TorchTPU for native PyTorch execution on Google TPUs. @awscloud announced TorchNeuron for AWS Trainium. TorchTitan expanded model support, improved training performance, and introduced reinforcement learning through TitanRL. The program featured more than 100 sessions and 144 poster sessions, alongside Day 0 training and workshops. In the Community Expo, attendees connected with sponsors, exhibitors, and core maintainers through booth conversations, demonstrations, and Meet the Developers. The 2026 PyTorch Contributor Awards recognized innovation, collaboration, and impact across PyTorch, @vllm_project, @DeepSpeedAI, Ray, Helion, and Safetensors. Explore the announcements, keynotes, technical updates, contributor recognition, and community highlights in our recap. Thank you to the contributors, maintainers, speakers, trainers, program chairs and committee, sponsors, and attendees who made #PyTorchCon possible. Read the recap: pytorch.org/blog/pytorch-con… Stay tuned for session slides and recordings, and save the date: PyTorch Conference returns to San Jose, October 6–7, 2027!