Elastic Expert Parallelism in @vllm_project lets you add or remove GPUs from an active Mixture-of-Experts deployment during traffic with minimal interruption to serving and minimal downtime. At #PyTorchCon North America 2026, Itay Alroy (@nvidia) will present “Elastic Expert Parallelism in vLLM,” covering the architecture, key implementation details, open challenges, and future roadmap for Elastic EP. Alroy will also examine what happens when EP size changes and how NIXL EP enables grow/shrink under live traffic. Register for PyTorch Conference North America 2026: hubs.la/Q04v4SL60

Debugging LLM training in production is notoriously challenging because subtle bitwise errors can surface long before they ever trigger a spike in the loss curve. Ziming, a PhD student at the University of Michigan and student researcher at @ByteDanceSeed_ , will speak at PyTorch Conference North America on how to solve this issue using OpGuard. OpGuard compares separate training runs bit by bit to pinpoint the exact initial operation where executions diverge. Join us in San Jose, October 20 to 21, to learn how bitwise alignment delivers faster, more precise LLM training debugging: hubs.la/Q04v4SL60 #PyTorchCon @UMich

Interested in optimizing Mixture of Experts LLM inference on ARM CPUs? In his talk at PyTorch Conference North America, Maajid Khan from Fujitsu Research India will explore efficient MoE LLM inference using vLLM and OpenVINO, sharing practical strategies for running these models effectively on ARM architectures. Register and join us in San Jose, October 20-21: hubs.la/Q04v4SL60 #PyTorchCon

To support developers, researchers, and engineers in deepening their technical skills, the PyTorch Foundation is running a dedicated Introduction Track at PyTorch Conference North America in San Jose, California, featuring the following speakers: @NVIDIA - Aastha Jhunjhunwala, Mark Moyou @RedHat- Lucas Wilkinson, Matthew Bonanni @HuggingFace - Aritra Roy Gosthipaty, Suvaditya Mukherjee @CrusoeAI - JanakiRam Goteti, Suman Debnath ETH Zurich - Andrea Mattia Garavagno @Harvard University - Vijay Janapa Reddi @CloudNativeFdn - Yashasvi Misra Additionally, an official, full-day PyTorch Associate Training session led by instructor Faradawn Yang will take place on Monday, October 19, 2026, offering hands-on labs, real-world projects, and a voucher for the PyTorch Certified Associate exam. Seats are limited, so register by Tuesday, October 13th to secure a spot and elevate your AI development skills. Read our latest blog to learn which sessions will feature at the Introduction track and how to sign up to the PyTorch Associate Training session: bit.ly/4dE9899

At #PyTorchCon North America 2026, @lizli202503 and @indianspeedster of @AMD will discuss their work enabling scalable MXFP8 pretraining on MI355X GPUs. Liz and Shekhar will cover optimization of key MXFP8 operators in TorchAO and how those kernels were integrated with TorchTitan to build an end-to-end upstream PyTorch training stack for large language models. Their session, “Scaling MXFP8 Pretraining on 1K+ AMD Instinct MI355X: TorchAO Kernels and TorchTitan Training,” will also cover Triton and FlyDSL implementations and lessons from numerical validation, convergence, and performance tuning. Join us in San Jose on October 20-21. Register today: hubs.la/Q04v4SL60

🤲 Open source moves forward when people build together. #PyTorchCon North America brings together the researchers, engineers, maintainers, and contributors doing exactly that - sharing what they've learned, working through challenges, and building on each other's work. Join the open source AI community in San Jose from Oct 20-21: bit.ly/4sh3DSw

🚨 Last Chance To Take The Stage At PyTorch Day Japan! The Call for Proposals closes this Sunday, September 27 at 11:59 PM JST. Bring your ideas and experiences to a community of PyTorch developers, machine learning engineers, AI researchers, and open source AI leaders from across Japan and beyond. ⏰ Submit Your Proposal >> bit.ly/4yuIMyz

At #PyTorchCon North America 2026, Alessandro Sangiorgi, Senior Software Engineer (@RedHat), will show how warm starts let Helion autotuning reuse cached configurations so developers can iterate faster instead of repeating cold searches. Sangiorgi will present “Accelerating Helion Autotuning with Warm-Start and Shared Caches,” a poster on Helion, a PyTorch DSL for GPU kernels. Join us in San Jose on October 20-21: events.linuxfoundation.org/p…

The PyTorch Foundation OSPO & Academic Outreach Working Group is inviting academic open source projects to submit for a Day 0 workshop at #PyTorchCon North America 2026. Projects using PyTorch, @DeepSpeedAI, Helion, @raydistributed, Safetensors, or @vllm_project can submit for consideration. Eight selected projects will present five-minute lightning talks, followed by a hands-on workshop and mentor office hours. Depending on the project, workshop conversations may cover open source readiness, governance, reproducibility, community, security and maintenance, and ecosystem positioning. The call is open to students, researchers, faculty, research engineers, university labs, academic OSPOs, research institutions, and maintainers of research-originated open source projects. The submission deadline is September 30, 2026, at midnight PT. Register for PyTorch Conference North America: hubs.la/Q04tBgv_0 🔗 Read more and submit: pytorch.org/blog/from-resear…

This just in! Take our live, in-person PyTorch Associate Training the day before PyTorch Conference North America in San Jose, CA on Monday, October 19th. Through a blend of lectures, demonstrations, guided labs, and assessments, you'll will not only become more familiar with PyTorch’s ecosystem but will also build and optimize real-world models from scratch. Upon completion of the course, you will also receive a voucher ($250 value) to take the new PyTorch Certified Associate (PTCA) certification exam. Learn more and sign up for this training at: hubs.la/Q04y8msv0 #PyTorchCon

Following a great community gathering at Graphcore's London office, momentum is building for PyTorch Conference North America 2026. Join PyTorch Foundation board member Sylvain Viguier and fellow open source developers, researchers, and technical leaders in San Jose, California on October 20 and 21. We look forward to hearing about your latest projects, sharing technical insights, and connecting in person. Register now to save your spot: hubs.la/Q04v4SL60 #PyTorchCon @graphcoreai

Open software. Open hardware. Open standards. Open data. Open benchmarks. If your Bay Area event advances open AI, it could be part of #OpenSourceAIWeek, October 16-25, featuring flagship events #PyTorchCon and #AGNTCon + #MCPCon. Submit to be a part of it all: bit.ly/4ipYZ39

How do you keep @vllm_project moving at the speed of light without excluding users who run diverse models on diverse hardware? In a new PyTorch Foundation blog, contributors from @IBM, @Meta, and @huggingface introduce hardware-agnostic layers designed to balance frontier performance with portability, helping ensure vLLM continues to meet the needs of the broader open source ecosystem. Read the blog to learn more: bit.ly/4xEH7Wk @hmellor_ @th_ortner

Where research meets real-world application. 🌎 At #PyTorchCon North America, hear from the researchers and practitioners advancing #PyTorch and putting those advances to work. See how ideas move from research into practical implementation and how what gets learned in practice helps shape what comes next. Join us in San Jose, Oct 20-21: bit.ly/4sh3DSw

PyTorch releases are no longer just about shipping PyTorch binaries. Release engineering now coordinates PyTorch, Triton, and @vllm_project as part of a broader ecosystem. At #PyTorchCon North America 2026, Andrey Talman (@Meta) will discuss how the PyTorch release process is being modernized, including the use of AI agentic workflows to analyze failures and the work required to release projects together with reliability and performance in mind. Hear more from Andrey about what he’ll cover at the conference. 🔗 Register: events.linuxfoundation.org/p…

Frontier models are the fastest way to launch an AI product, but what happens when usage scales? In our latest case study, @Shopify shares how they built a continual learning loop using @PyTorch and @vllm_project for their GraphQL agent, turning everyday production failures directly into model weight improvements. Read the full breakdown by Cody Mazza-Anthony and @Drewch to learn more about they define quality, calibrate judges, and distribute training across GPUs: pytorch.org/blog/how-shopify… Plus, don't miss the @ShopifyEng keynote at #PyTorchCon NA on how small models can outperform frontier models on well-scoped tasks at a fraction of the cost, with lower latency and higher throughput. Get your ticket for PyTorch Conference North America (October 20-21 in San Jose, CA): hubs.la/Q04v8Lq_0

Every mature systems project eventually needs a teaching version. TinyTorch is a free, open source curriculum where you build a working machine learning framework from scratch, tensors through transformers, using PyTorch’s own API in pure Python. It requires no GPU, runs on a 4 GB laptop, and covers 20 hands-on modules designed to give developers, students, and engineers a complete mental model of PyTorch internals. Read the full technical breakdown here: bit.ly/4ArNTRO @profvjreddi

RL post-training has become a critical stage in modern LLM development, but deploying an end-to-end pipeline requires much more than running individual kernels efficiently. Systems must coordinate distributed training, rollout generation, and continuous weight synchronization across multiple software stacks while maintaining correctness and performance. @JoySong351749 with @AMD will present a poster at PyTorch Conference North America on enabling the open source vime RL post-training framework on AMD Instinct GPUs using ROCm. Register for PyTorchCon NA at: hubs.la/Q04v4SL60 #PyTorchCon

#PyTorch meets TPUs, Trainium, edge devices, resilient training, and more. ⚡ Catch quick live demos in the #PyTorchCon North America Community Expo, October 20-21 in San Jose. Plan your stops: bit.ly/4hb0ekq Register: bit.ly/4sh3DSw

Join Valerian Rey from Simplex Lab at PyTorch Conference North America 2026 as he breaks down multi-objective optimization. He will share practical techniques for training models with multiple loss functions simultaneously and demonstrate how to easily implement these workflows using the TorchJD library. Whether you are optimizing multi-task architectures or managing complex loss tradeoffs, this session will provide concrete steps to streamline your pipeline. Join the open source AI community in San Jose, October 20-21 : hubs.la/Q04v4SL60 #PyTorchCon

At PyTorch Conference North America in San Jose, Arkadip Maitra from the PyTorch engineering team at @RedHat will present two technical poster sessions covering key topics in inference performance and testing infrastructure. Connect with the open source AI community on October 20-21 to discuss open source runtime performance, hardware optimization, and testing frameworks. Register for PyTorch Conference America today: hubs.la/Q04v4SL60 #PyTorchCon @arkadipmaitra

At PyTorch Conference North America 2026 in San Jose, @RedHat engineers Jewel Muraledharan and Subin George Malana will present on Cross-Repository CI Relay (CRCR) to explore how downstream repositories can seamlessly integrate into upstream PyTorch CI. Their session will detail how CRCR enables a tiered onboarding model alongside real-time visibility for downstream repositories in HUD. Join us in San Jose on October 20 and 21 to learn how CRCR streamlines testing workflows across the ecosystem. Register today: hubs.la/Q04v4SL60 #PyTorchCon

At PyTorch Conference North America, explore how new optimizers like Muon and TorchJD work alongside tools like fastsafetensors and LMCache to drive multi-loss efficiency and faster LLM serving. Featured speakers include: @awscloud : Paulo Aragao @Arm : Thomas Cottenier @Google : Claudio Basile, Aleksey Vlasenko, Ankita Luthra, Trinadh Kotturu @huggingface : Ben Burtenshaw, Aritra Roy Gosthipaty, Suvaditya Mukherjee @Huawei : Jiahao Chen, Jiahao Tan @IBM : Takeshi Yoshimura, Prasanth Chatarasi, Bardia Mahjour, Viji Srinivasan, David Grove, Antoni Viros Martin, Avery Blanchard @intel : Panagiotis Kourdis, Tanima Dey @Meta : Felipe Mello, Jiani Wang, Will Constable, Natalia Gimelshein, Driss Guessous, Sanket Jayant Purandare, Aditya Venkataraman, Nicolas Hug, Scott Schneider, Edward Yang @nvidia : Ian Stenbit, Christine Cheng, Dylan Doblar Annapurna Labs (AWS subsidiary): Yahav Biran @argonne National Laboratory: Sam Foreman Beijing Academy of Artificial Intelligence: Yonghua Lin Bird of Paradise AI: Jennifer Wei @BytedanceTalk : Neiwen Ling @Harvard University: Vijay Janapa Reddi @RedHat Hat: Subin George, Jewel K M SimplexLab: Valérian Rey; Khush Patel @tensormesh : Kuntai Du University of Genoa: Andrea Mattia Garavagno University of Virginia: Tianle Zhong Join us in San Jose, October 20-21: hubs.la/Q04tBgv_0 Read the Open Research, Tooling & Optimization Sessions Guide here: bit.ly/4gXxn4r #PyTorchCon

Muon has attracted a lot of attention for fast convergence, but getting those optimizers to work in a real training stack is a different challenge. At PyTorch Conference North America, @JenniferWe17599 will walk through Muon, Dion, and Dion3 and look at what happens when you add the messy details: sharding, communication, schedulers, and everything else that can go wrong. If you are interested in optimizers and training dynamics, see you at PyTorchCon NA for Jen's talk on Beyond AdamW: A Practical PyTorch Walkthrough of Muon, Dion, and Orthogonalized Optimizer Variants. Get your ticket: hubs.la/Q04v4SL60

The first-ever PyTorch Day Japan comes to Tokyo on December 10, bringing the community together to explore PyTorch, @vllm_project, @DeepSpeedAI, @raydistributed, Helion, and Safetensors. Co-hosted by PyTorch Foundation, @huggingface, @IBM, and @ME_JP_official, the event will feature technical talks and interactive discussions across open source AI, including training, inference, responsible AI, physical and edge AI, open model development, and the broader PyTorch ecosystem. The call for proposals is open for session presentations and lightning talks through September 27 at 11:59 PM JST. Register today! 🔗 Read more: pytorch.org/blog/pytorch-day…

↘️ Deep technical content. Meaningful conversations with people solving the same problems. At #PyTorchCon North America, go deeper into #PyTorch features, optimization, deployment, and more then continue the conversation with developers and researchers doing the work. The talks matter. So do the conversations you can only have in the room. Join us Oct 20-21 in San Jose: bit.ly/4sh3DSw

At PyTorch Conference North America 2026, Dhritiman Das, Staff Software Engineer - Machine Learning Infrastructure (@LinkedIn), will present a torch-native retrieval engine that uses PyTorch as the primary runtime for retrieval, filtering, and ranking. The system combines a GPU-resident torch tensor index, tensor-based retrieval operations, custom CUDA kernels for attribute filtering, and TorchScript model execution within a unified serving architecture orchestrated through a Rust and tch-rs backend. Dhritiman will also share how the approach scales to critical use cases like feed and search at LinkedIn. Join us in San Jose on October 20-21: hubs.la/Q04v4SL60 View the poster sessions: events.linuxfoundation.org/p… #PyTorchCon

Live demos. Big ideas. Zero slide-deck suspense. 👀 See #PyTorch technology in action at the Demo Theater in the #PyTorchCon North America Community Expo, October 20-21 in San Jose. Explore: bit.ly/4hb0ekq Register: bit.ly/4sh3DSw

Engineering teams from across the ecosystem are presenting major breakthroughs in torch.compile, custom kernel authoring, and scaling efficiency at the upcoming PyTorch Conference North America. Deepening performance across the compiler pipeline requires tackling bottlenecks at every layer, from front-end tracing and shape checking, to back-end execution and distributed orchestration. A few of the speakers sharing their insights include: @AMD: Liz Li, Prachi Gupta @huggingface: Sayak Paul @Huawei: Yun Zhao; Haonan Zhang @IBM, @IBMResearch: Olivier Tardieu, Matthew Arnold, Burkhard Ringlein @Intel: Xiaogang Gu, Qun Yang, Whitney Tsang, Artur Fierka, Panagiotis Kourdis, Tanima Dey @Meta: William Wen, Steven Troxler, Avik Chaudhuri, Elias Ellison, Laith Sakka, Angel Li, Richard Zou, Yidi Wu, Oguz Ulgen, Dunfan Lu, Jason Ansel, Jongsok Choi, Ethan Che, Kaiming Cheng, Laura Wang, Driss Guessous, Simon Layton, Marius Eriksen, Wei Feng, Anshul Sinha, Ailing Zhang, Bob Ren, Aaron Orenstein, Chien-Chin Huang, Pian Pawakapan, Sanket Jayant Purandare, Francisco Massa, Tristan Rice, Kapil Sharma, Natalia Gimelshein, Ben Carver @NVIDIA: Daniel Galvez, Michael Goldfarb, Guray Ozen, Ke Wen, Sreeram Potluri, Artem Polyakov, Anjulie Agrusa, Ryan Spring, Bruce Zitelli @anyscalecompute : Masahiro Tanaka @CrusoeAI: Suman Debnath, JanakiRam Goteti @UCBerkeley: Yi Pan University of Washington (incl. Paul Allen School): Megan Frisella, Stephanie Wang PyTorch Conference is the open source AI community's town square. Where what's next gets decided. Register now to join the open source AI community in San Jose, October 20-21: bit.ly/464FTbp Read the Open Research, Tooling & Optimization Sessions Guide here: bit.ly/4gXxn4r #PyTorchCon

New from @Meta Engineering: FlashAttention-4 extended with MXFP8 support for @nvidia Blackwell—from forward and backward kernels to fused quantization and jagged cross-attention. The team developed an end-to-end jagged module with fused quantization, FP8 activation and compute which is being used internally at Meta for GEM training. On the latest gen hardware, LP FA4 kernel reaches 2.85 PFLOP/s forward and 2 PFLOP/s backward, with up to a 1.30× end-to-end module speedup. ✍️ Devashish Shankar, Santosh Mohan, Jiaqi Xu, Darren Liu, Han Xu Explore the design and open source implementation in our latest blog: pytorch.org/blog/low-precisi…

More visibility. New audiences. One seriously intelligent week. 🧠 Bring your Bay Area event into the #OpenSourceAIWeek lineup, October 16-25, alongside flagship events #PyTorchCon and #AGNTCon + #MCPCon in San Jose. Submit by October 15: bit.ly/4ipYZ39

At #PyTorchCon North America 2026, Sudhanshu Shrivastava, Graduate Student Researcher, Electrical and Computer Engineering, @ucdavis, will present a federated learning case study in glaucoma imaging using 5,550 color fundus photographs from nine datasets across seven countries. Sudhanshu will discuss how federated learning enables collaborative medical imaging research without data centralization, with practical lessons on site-specific fine-tuning, cross-site generalizability, and multi-site learning. Join us in San Jose on October 20-21: hubs.la/Q04v4SL60 #PyTorchCon

New chips are shipping faster than ever before, but the ecosystem is being held back by having to rewrite and then re-debug the same code over & over again. @clattner_llvm CEO and Co-founder at @Modular and EVP of Advanced AI Software & Platforms at @Qualcomm, will deliver a keynote at PyTorch Conference North America about an open software platform for heterogeneous compute powered by Mojo and MAX. PyTorch has always been the place where the best models come together, and now there's a way to get those models onto all kinds of hardware. If you're interested in Al and compute, join us at the PyTorch Conference in San Jose, CA. Register now: hubs.la/Q04v4SL60 #PyTorchCon

🎤 Meet Keynote Speaker Colin Brace, VP of Annapurna Labs at @awscloud. At #PyTorchCon North America, Colin will present “Trainium’s Journey to Native PyTorch,” sharing how #PyTorch now runs natively on AWS Trainium with no code changes required. Hear how AWS enabled eager mode and torch.compile, integrated Trainium with TorchTitan, TorchAO, and Hugging Face Transformers v5, and contributed upstream to the PyTorch ecosystem. 📅 October 20-21 📍 San Jose, California Join the PyTorch community - register today: bit.ly/4sh3DSw

Learn how PyTorch can extend language modeling beyond classification to practical time-to-event prediction. Witold Czubala of @UBS will share a PyTorch-based transformer model that predicts six-month attrition from longitudinal advisor–client email communications for wealth management during PyTorch Conference North America in San Jose, CA. Join us October 20-21: hubs.la/Q04v4SL60 #PyTorchCon

🍎 Fresh ideas. 💬 Relevant technical conversations. 💡 Insights from the people doing the work. That’s what attendees have come to expect from #PyTorchCon North America, taking place Oct 20-21 in San Jose. Join the open source AI community for keynotes, technical talks, hands-on sessions, and candid conversations about the work shaping AI today. bit.ly/3Ra1oUx Register: bit.ly/4sh3DSw

"It's really great to feel the energy and see all the collaboration that's happening, lots of conversations. We have people here who are just starting to learn about PyTorch, and we have people who are maintainers. It's super nice to see that energy and see how together we're going to be able to solve some of these very difficult problems for humanity." Ankit Patel, @nvidia, at PyTorch Conference Europe 2026 Register today to join the open source AI community at PyTorch Conference North America in San Jose, October 20–21: hubs.la/Q04tBgv_0 #PyTorchCon

The open source AI community thrives on collaboration, choice, and open contribution. As Joseph Groenenboom from @RedHat highlights, empowering developers to freely contribute and build options is essential for growing the entire AI ecosystem. PyTorch Conference North America 2026 is where that community comes together in person. Join us to collaborate with open source pioneers, expand your deployment capabilities, and directly contribute to shaping the future of machine learning. Register for PyTorch Conference North America today: hubs.la/Q04tBgv_0 #PyTorchCon

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

The @huggingface Kernels project now has Helion support. This blog walks through how to build, autotune, and ship performant and portable Helion kernels via the Hugging Face Kernels project, allowing users to consume these kernels seamlessly. Learn more here: bit.ly/4d9UOF6

PyTorch 2.14 introduces updates to Inductor, PyTorch Distributed, c10d, dynamic shapes, Apple Silicon, and accelerator platform support, with 2,995 commits from 487 contributors since PyTorch 2.13. Bring your questions about PyTorch 2.14 to our live Q&A on Thursday, September 17, 2026. Andrey Talman (@Meta), Natalia Gimelshein (@Meta), @joespeez (@reflection_ai), and Chris Gottbrath (Gottbrath Tech), moderator) will share an overview of PyTorch 2.14 and answer community questions about PyTorch and the new capabilities. Register here: pytorch.org/event/pytorch-2-… PyTorch 2.14 covers: - NVGEMM and CuTeDSL-generated CUTLASS kernels in Inductor - The new nccl2 backend for PyTorch Distributed - Fault-tolerant collectives and process-group reconfiguration in c10d - Native linear algebra and additional Metal kernel improvements on Apple Silicon - torch.switch and CUDA graph capture for torch.while_loop - Declarative dynamic shapes with @dynamic_spec - Experimental torch.compile support for complex-valued tensors - Expanded ROCm, Intel XPU, and NVIDIA platform support Want to learn more about compiler and runtime work, distributed communication, device portability, accelerator integration, and more? Register for PyTorch Conference North America 2026, where engineers, researchers, and maintainers will convene October 20–21 in San Jose: hubs.la/Q04tDbKG0 #PyTorchCon

Bay Area AI event organizers, your week just got bigger. 🤖 Submit your conference, hackathon, meetup, startup showcase, or networking event to join #OpenSourceAIWeek, October 16-25. Flagship events: #PyTorchCon and #AGNTCon + #MCPCon Apply by October 15: bit.ly/3KjXQv2

🏋️ Train smarter. From distributed training to optimization techniques and foundation models, the Training Track at #PyTorchCon North America, Oct 20-21 in San Jose, is packed with practical sessions to help you build faster, more efficient AI systems. Learn more: bit.ly/4cVqz4X 📅 Schedule: bit.ly/3Ra1oUx 🎟️ Register: bit.ly/4sh3DSw

At PyTorch Conference North America 2026, Nicolò Lucchesi, Research Engineer at @MistralAI and vLLM maintainer, will present joint work with @AWS and @RedHat on how disaggregated serving in vLLM has evolved to support the latest generation of hybrid models. This session will cover the evolution of disaggregated serving for modern hybrid architectures, protocol developments aimed at reducing end-to-end latency, and new key-value pinning mechanisms designed for reliability at scale. Join us in San Jose on October 20-21: hubs.la/Q04v4SL60 #PyTorchCon @vllm_project

The PyTorch Korea User Group will host its inaugural offline conference on Saturday, November 21, 2026, hosted at AWS Korea in Centerfield East, Seoul. Designed around the end-to-end AI lifecycle, the event features three primary tracks: Build, Serve, and Run. Community members, developers, and researchers are invited to submit session proposals highlighting real-world project wins, takeaways from failed experiments, or core performance optimizations. The deadline to submit proposals is Sunday, September 13, 2026, at 23:59 KST. Submit your talk today: bit.ly/4iVlME7

PyTorch Day Japan 2026 comes to Tokyo on December 10, and the call for proposals is officially OPEN! We're accepting proposals for session presentations and Lightning Talks across the full spectrum of open source AI, PyTorch, and AI/ML. Suggested topics include: 🚀 Sovereign AI (Local & Open Models) 🏋️ Physical AI & Edge AI 💡 PyTorch Ecosystem Submit a Proposal by September 27 at 11:59 pm JST >> bit.ly/4yuIMyz