🚨 3 days left! The OSPOlogy + #OSPOSummit# China #CallForProposals# closes July 12. Bring your insights on #OpenSource# governance, community growth, compliance, developer engagement, & organizational strategy to Shanghai this September 7.

PyTorch 2.13 is here, with 3,328 commits from 526 contributors and updates across FlexAttention, CuTeDSL, nn.LinearCrossEntropyLoss, torchcomms, FSDP2, Python 3.15 wheels, ROCm, Arm, and XPU. The release blog and notes cover FlexAttention on Apple Silicon with up to ~12x speedup over SDPA on sparse patterns, a deterministic backward path on CUDA, the CuTeDSL "Native DSL" backend for Inductor, nn.LinearCrossEntropyLoss to reduce peak GPU memory by up to 4x, torchcomms for large-cluster training, and FSDP2 communication overlap improvements. On July 22 at 11 a.m. PT, join @albanDesmaison (@Meta), Andrey Talman (@Meta), Piotr Bialecki (@NVIDIA), and Chris Gottbrath for a live 2.13 Q&A. 🔗 Read the release blog, and register for the live Q&A:

Joseph Gabriel Lagonsin (ITBrief) reports on Shopify’s Platinum membership in PyTorch Foundation, including Shopify’s plans to contribute upstream engineering expertise and share experience from running machine learning systems in retail and commerce settings. "AI is becoming the operating layer for commerce, and we're convinced that layer needs to be open to reach global scale," said Mikhail Parakhin, Chief Technical Officer, Shopify. "PyTorch is central to how Shopify builds AI today. Joining the Foundation lets us invest in that base directly and help shape it for the agentic era, rather than just building on top of it." The coverage also details Shopify’s use of PyTorch across Sidekick, search and recommendation tools, fraud protection, and foundation model work tied to merchant tools. "We are excited to welcome Shopify to the PyTorch Foundation as our newest Platinum Member," said Mark Collier, Executive Director, PyTorch Foundation. "Shopify operates where AI meets real buyers and sellers every day, and that vantage point is exactly what the Foundation needs as agents become a front door to commerce. Read more:

Foundation models are reshaping computational biology. Adapting models to a specific task is nontrivial, so to reduce the difficulty of building these workflows, @nvidia BioNeMo Recipes provide step-by-step training recipes built on familiar PyTorch, Hugging Face, and other patterns. This post walks through two case studies that show how the same parameter-efficient and readable recipe applies across biological modalities. Read the full post:

New on the PyTorch Foundation blog: @AMD and @Meta contributors share how PyTorch Monarch was brought to AMD Instinct GPUs with ROCm to support fault tolerant distributed training at scale. The post walks through the ROCm port of Monarch’s GPU runtime and distributed communication stack, then shows how Monarch, TorchFT, and TorchTitan enable healthy replicas to continue training while failed nodes recover and rejoin without a full checkpoint restart. Validation includes Llama 3 8B training on a 128 GPU AMD Instinct MI300 SLURM cluster and a 256 GPU AMD Instinct MI355 Kubernetes cluster. Read the full technical deep dive:

🚀 Build, benchmark, optimize, & connect with the global #PyTorch# community at #PyTorchCon# North America! Join us October 20-21 in San Jose, CA for two days of technical talks, hands-on learning, & conversations shaping the future of #AI#. 💰 Register by July 31 to save $400:

As Europe’s AI sovereignty debate draws more attention to models, @tech_eu examines PyTorch’s role in the open source infrastructure that supports them. Cate Lawrence (@tech_eu) spoke with Mark Collier, Executive Director, PyTorch Foundation, about PyTorch as a common software layer for open-weight AI, neutral governance for critical AI infrastructure, and PyTorch Foundation’s expanding role as a home for projects including @vllm_project, @DeepSpeedAI, @raydistributed, and Helion. The article also covers SafeTensors moving toward community stewardship under PyTorch Foundation. As Lawrence writes, “For Collier, Europe's competitive advantage isn't simply producing more AI models — it's helping build the open infrastructure that allows an entire ecosystem of companies to innovate.” 🔗 Read it here:

⏳ 5 days left to submit! The #CallForProposals# for OSPOlogy + #OSPOSummit# China closes July 12. Share your experiences with OSPO strategy, governance, compliance, community management, #OpenSource# culture, & more. 📍 Shanghai | September 7

PyTorch Foundation supported the ExecuTorch Hackathon in San Francisco, where more than 100 participants across 20+ teams built real-time AI applications using PyTorch and ExecuTorch. Teams built on Snapdragon-powered Samsung Electronics Galaxy S25 Ultra devices, focusing on latency, offline capability, privacy-sensitive processing, energy efficiency, and real-time user experience. Congratulations to the winning teams: 1st Place: SafeScreen AI, an on-device visual safety layer 2nd Place: SixthSense, an assistive wearable that converts visual information into directional haptic signals 3rd Place: Toddle AI, a privacy-first prototype for analyzing toddler walking patterns locally The winning projects showed how local execution can support applications that require immediate feedback, limited connectivity, or sensitive data processing. Read the full recap from @matthew_d_white (PyTorch Foundation), Andrew Caples (@Meta), and Lauren Lunde (@Qualcomm):

🚀 Your next big #OpenSource# conversation starts in Shanghai. Join #KubeCon# + #CloudNativeCon# + #OpenInfraSummit# + #PyTorchCon# China, September 7-9, for three days of technical sessions, community collaboration, & the ideas shaping the #AI# era. ⏰ Register by July 28 to save ¥710 RMB:

PyTorch Foundation is a Gold Sponsor of Agentic AI Summit 2026. Matt White, CTO of PyTorch Foundation, will lead “The Open Agentic Stack,” on building AI systems with open source, open standards, and composability. 🔗

Welcome @MParakhin and @ShopifyEng ! This is another signal that companies will train and serve *many models* with @PyTorch & that open source is the only way to do it. Shopify knows production system at scale, and the whole community will learn & improve together in the open!

🎓 Students, researchers, & practitioners: Share your work with the #PyTorch# community at #PyTorchCon# North America, October 20-21 in San Jose, CA. Poster proposals are due July 26:

#OpenSource# doesn't scale by accident. Share how your organization approaches governance, contribution strategies, security, compliance, community engagement, & more at OSPOlogy + #OSPOSummit# China. 📅 September 7, Shanghai 🎤 Submit to speak by July 12:

PyTorch-native NeMo AutoModel handles transformer pretraining in @nvidia's end-to-end workflow for building a transaction foundation model. The workflow combines GPU-accelerated data processing and tokenization, decoder-only model pretraining, embedding extraction, and XGBoost fraud classification. On the synthetic @IBM TabFormer dataset, combining raw features with learned embeddings increased Average Precision by 41.76% over the raw-feature baseline. 🔗 Read the full post:

Built on PyTorch, Ray, SGLang, and NVIDIA Megatron-LM, Miles is an open source framework from RadixArk for large-scale LLM reinforcement learning post-training. Miles uses PyTorch for models, numerics, profiling, and extensibility; Ray for orchestration; SGLang for rollout generation; and Megatron-LM for distributed training. The framework supports asynchronous rollout and training, NCCL/RDMA weight synchronization, MoE-aware rollout/training alignment, low-precision recipes, LoRA, fault tolerance, observability, and extension points for custom algorithms and model architectures. 🔗 Read more in our latest blog from the Miles Team:

💡 Research. Engineering. #OpenSource# collaboration. Experience it all at #PyTorchCon# North America, October 20-21 in San Jose, California. ⏳ Early bird savings of $400 end July 31. Register now:

Deploying AI models at the edge comes with a different set of challenges. These hands-on Jupyter labs walk you through using ExecuTorch to deploy and optimize @PyTorch models on Arm CPUs and NPUs, with examples you can run on hardware including Raspberry Pi. 

“Open source foundations exist to create the conditions for the industry to do hard work together that no single organization can do alone. Security is no different. AI has fundamentally changed the math on vulnerability discovery, and going it alone is no longer just inefficient; it's dangerous. Efforts like Akrites pave the way for the widest possible participation and the largest possible impact.” Mark Collier, Executive Director, PyTorch Foundation @sparkycollier Read the Akrites open letter: Learn how to get involved:

Huge milestone from the @anyscalecompute + @googlecloud GKE teams 🎊 Ray Serve LLM provides up to 4.4x higher throughput on prefill-heavy workloads and 24x on decode-heavy workloads than previous versions. Three optimizations made this possible on the Ray Serve LLM + vLLM stack: ⭐️Direct streaming with a control-plane-only endpoint picker ⭐️ A new vLLM Ray V2 executor backend ⭐️HAProxy ingress for routing at the speed of C Ray's primitives for fault tolerance, observability, and portability across K8s and VMs are a great foundation as inference deployments get more complex. Congrats to the team! Try the new Ray V2 executor today in vLLM with --distributed-executor-backend ray.