In the latest of our Community Builds, we are thrilled to highlight Charakuru, an incredible open-source kit by @Dstudio_ai powered by Tripo P2.0. ✨ See how it works, download it for free, and get ready for our Halloween event!

No single project, company, or community builds the AI stack alone. Behind the models, frameworks, cloud native technologies, & infrastructure powering AI is a global open source community working across every layer. Jane Lyu of @linuxfoundation, Fupan Li of @AntGroup, @Zesheng_Zong of @Huawei, Sunny Chan of TCC demonstrate how collaboration between projects & communities turns individual technologies into an open, interoperable AI ecosystem at #KubeCon# #OpenInfraSummit# #PyTorchCon# China 2026 @CloudNativeFdn @openinfradev @PyTorch

We’ve just released the #Alpamayo# Chain-of-Causation (CoC) Autolabeling Pipeline — a feature that has been highly requested by the community! The pipeline automatically derives: 🔹 Meta-actions: high-level categorical descriptions of ego motion 🔹 Chain-of-causation labels: causal links between scene factors and the ego vehicle’s intended behavior Autolabeling pipeline: Learn more about the Alpamayo open platform: We’re excited to see what the community builds with it, and we hope this tool will help accelerate research in the rapidly growing area of #reasoning# models for #Physical# #AI#. @NVIDIADRIVE @NVIDIAAI

KubeCon + CloudNativeCon + OpenInfra Summit + PyTorch Conference China 2026 brought the people working across the open source AI stack together in Shanghai. @sparkycollier No single project, company, or community builds the AI stack alone. Behind the models, frameworks, cloud native technologies, and infrastructure powering AI is a global open source community working across every layer. PyTorch Foundation welcomed @alibaba_cloud and Cambricon (寒武纪) as Platinum Members and @AntGroup as a Gold Member, joining @Huawei and other existing Foundation members. Across the program, maintainers, researchers, developers, hardware vendors, and technical leaders discussed PyTorch, distributed training, inference and serving, heterogeneous hardware, cloud native infrastructure, accelerator integration, and agents, with participation from the @CloudNativeFdn and @openinfradev communities. Our recap covers keynotes from across the open source AI stack, China-based PyTorch contributors and organizations, the PyTorch TAC Accelerator Integration Working Group, the Foundation press conference, and community conversations in Shanghai. PyTorch conferences are the open source AI community’s town square, where what’s next gets decided. If you couldn’t join us in Shanghai, PyTorch Conference North America 2026 is the next chance to hear directly from maintainers, researchers, developers, and AI engineers working across the open source AI stack. PyTorch Conference North America comes to San Jose October 20–21, with maintainers from PyTorch, @vllm_project, @DeepSpeedAI, and @raydistributed among the speakers. 🔗 Read the Shanghai recap and register for PyTorch Conference North America 2026: #PyTorchCon# #KubeCon# #CloudNativeCon# #OpenInfraSummit#

One of our biggest fans has 530,000 people in his Facebook group. What if they all had a room at my conference? Jessica has been building our referral rewards. Rewards money can't buy. Her next steps: run the plan past our operations team, and get Joel to sign people up for the referral program the moment they buy a ticket. My worry: I would hate to take on a lot of costs and then not have a lot of people be part of it. Then I showed her my call with Jonathan Mast. He offered to bring his AI community to Social Media Marketing World. I offered him a private room on day one, just for his people. Jessica's first reaction: "That sounds like maybe it could be part of one of the incentive tiers too." Here's the key to the whole thing. Nobody gets into that room without a ticket. That's kind of a big development. Now Jessica goes back through the 200 and some ideas you've sent us to find what we do next. If there were a meetup just for your community, would that get you there? Reply "Yes" or tell me what would. Press Start: The Road to 3,000. #SocialMediaExaminer# #SMMW27# #RoadTo3000# #CommunityBuilding# #EventMarketing#

Yellowstone Vixen v0.7.0 is out 🚀 This release is all about making production indexing more reliable while improving data completeness. Highlights: • Jetstreamer upgraded to v0.5 Block rewards now forwarded Block entries included Built-in stats tracking Graceful shutdown support • Yellowstone gRPC now auto-reconnects by default with replay-aware recovery (when supported by the server), making transient outages much less painful. • Block coordinator is significantly more resilient: Better historical backfill Correct skipped-slot handling Handles late arriving records • Runtime rewritten with a native worker pool for bounded concurrency and much cleaner shutdown semantics. • Proc macro migrated to codama-rs events, bringing numerous parser fixes, SPL Governance support, improved Kafka error reporting, and more robust IDL generation. • New downstream APIs: InstructionUpdate::direct_log_messages() Flat instruction indexes • Added pToken instruction support. There are a few breaking changes for projects constructing config structs directly (JetstreamSourceConfig and YellowstoneGrpcConfig), but existing config files continue to work thanks to serde defaults. Thanks to everyone who contributed! Looking forward to seeing what the community builds with it.

One of our viewers called me with an offer. I didn't ask him to. Jonathan Mast comments on almost every single episode of this show. He told me, "You didn't even ask me to do this. I'm the one that reached out." He has a community he'd love to get excited about Social Media Marketing World. So we got on a call to find a way to collaborate that's mutually beneficial for both of our communities. His idea: a virtual lunch before the event. People get to ask questions, and more importantly, we have some fun with it. My first reaction: I really like the idea. Then I threw one back. What if I gave him a space at the event on the very first day? A room with a bunch of tables, exclusive just for him and his community. The one catch: they need a physical ticket to get in. His answer: "I think that'd be amazing. Let's do it." Here's why I think it works for both of us. He has an incredibly loyal community of people who are very excited about AI. I have what I believe are the world's best trainers on AI. And Jonathan said the part I keep coming back to: "Something special happens when we sit down next to each other." Nothing is decided yet. I'm taking it to my team. Should we team up? Tell me in the comments 👇 Press Start: The Road to 3,000. #SocialMediaExaminer# #SMMW27# #RoadTo3000# #CommunityBuilding# #EventMarketing#

We have just released #Alpamayo# 2 Super — @nvidia’s frontier open reasoning model for #autonomous# #vehicles#. NVIDIA Alpamayo 2 Super is an open 34-billion-parameter #reasoning# vision-language-action (#VLA#) model designed to accelerate autonomous vehicle (AV) development. It combines the 32-billion-parameter NVIDIA #Cosmos# 3 Super Reasoner with a 2-billion-parameter diffusion-based Action Expert and is post-trained with #reinforcement# #learning#. Two aspects make Alpamayo 2 Super particularly exciting: 1. Open and commercially deployable: Alpamayo 2 Super is available on Hugging Face under OpenMDW-1.1, the Linux Foundation’s permissive license for open AI model distribution. The OpenMDW license is now being applied across the entire Alpamayo model family, enabling developers to deploy these models commercially without requiring additional permissions. 2. A multi-task foundation model for autonomous driving: Alpamayo 2 Super produces five tightly coupled outputs: - A trajectory describing the vehicle’s planned path. - A chain-of-causation (CoC) trace explaining the reasoning behind each driving decision, achieving benchmark-leading reasoning performance at frontier scale. - A meta-action (e.g., yield, lane change, stop) capturing the model’s intent. - Reasoning auto-labels that generate CoC annotations for training and validation data. - Visual question answering responses with 2D visual grounding, linking answers to specific regions in camera images. These multi-task capabilities enable developers to leverage a single foundation model across more of the development process, simplifying tooling and accelerating iteration. Resources: 🔹 Interview: 🔹 Video: 🔹 Blog: 🔹 Technical blog: 🔹 Hugging Face blog: 🔹 Model weights: 🔹 Inference code: As @JensenHuang has emphasized, open models help advance safety and security. We hope Alpamayo 2 Super will contribute to this vision by enabling researchers and developers around the world to build, experiment, and innovate in autonomous driving. We are excited to see what the community builds with Alpamayo 2 Super. @NVIDIADRIVE @NVIDIAAI