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#

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.

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

AI agents are everywhere at @Uber. It’s great to see, but the thing that keeps me up at night is how we are going to secure them. This is something that I have been thinking about for a while. Today, our agents run 50,000+ sessions per day across thousands of endpoints. And this isn't just engineering anymore. Employees across the company use agents that read code, run commands, call internal tools, analyze data, and act on real systems. That scale forced us to confront an important question: How do you secure agents when your security tools can't even see them? Traditional Endpoint Detection & Response (EDR) sees the file write, but not the prompt that triggered it. It sees the network call, but not the agent's reasoning. The intent, the thing that separates malicious from benign, is invisible. So we built Agentic Detection and Response (ADR): • Capture the full causal chain: prompt → reasoning → tool call → outcome, across Cursor, Claude Code, Codex, and every agent our employees use. • Triage cheaply: a fast, high-recall first pass handles the flood of benign sessions. • Reason deeply: only suspicious events get expensive LLM analysis, enriched with source code, threat intel, and policy context. • Red-team continuously: an offline explorer evolves hard attack variants before attackers find them. After 10+ months in production, the results speak for themselves: • Hundreds of credential exposures detected across 26 categories. • Shift-left prevention blocking secrets at 97.2% precision, before they ever leave the laptop. • Zero false positives on our enterprise benchmark, with 2-4x the F1 score of state-of-the-art baselines. • Every attack detected on AgentDojo, the public prompt injection benchmark. Just as valuable as the detections are the lessons from running this in production: • The workflow is the unit of security, not the individual tool call. Attacks hide in causally-linked chains that look benign step by step. • Credential leakage is a far more common operational issue than prompt injection. • Approval fatigue is real: when users approve 50+ actions per session, human oversight becomes a rubber stamp. You can't secure agents you can't observe. And nobody can solve this alone. That is why we recently joined the Open Secure AI Alliance (OSA), and why today we're taking the next step: open-sourcing ADR. The release includes the ADR Sensor, the detection framework, and ADR-Bench, the first enterprise agentic AI security benchmark: 302 tasks derived from real production telemetry and full coverage of all 17 attack techniques across 5 tactics, so the community can rigorously evaluate their own defenses. Code: Paper: The future of AI security won't be built behind closed doors. Excited to see what the community builds on it, and what we all learn together! @UberEng

🏢 Throwback to a few days ago — we were incredibly fortunate to receive an invitation to visit the OKX Türkiye office in Istanbul. 🇹🇷 Beyond seeing one of the world’s leading exchanges up close, we also had the opportunity to sit down with the OKX Türkiye team for a discussion that I believe will be highly valuable for founders, builders, project teams, and communities looking to expand into the Turkish market. Turkey is one of the most active crypto markets globally, yet many international projects still don’t fully understand what drives the local community. So instead of focusing on token prices or market predictions, we asked questions that truly matter: 🔹 What makes the Turkish crypto community unique? 🔹 What can Asian projects and builders learn from Turkey? 🔹 What do Turkish users look for before supporting a project? 🔹 How can projects build long-term trust and credibility in the market? 🔹 What qualities define a “high-quality project” from the perspective of a leading exchange? 🔹 How can exchanges like OKX Türkiye potentially support projects and communities entering the region? The answers were insightful, practical, and in some cases, quite different from what many people might expect. If you’re a founder, builder, community leader, or project team looking at Turkey as your next growth market, you’ll definitely want to watch this one. 🎥 Full interview coming soon. A huge thank you once again to the OKX Türkiye team for the warm hospitality, valuable insights, and generous invitation. Stay tuned. 👀🔥 #OKX# #OKXTurkiye# #Turkey# #Web3# #Crypto# #Blockchain# #IBW2026# #CommunityBuilding# #Web3Growth#