Following up on my previous post about PhD Research Intern opportunities, the Autonomous Systems and Physical AI Research (ASPIRE, research.nvidia.com/labs/asp…) group at @nvidia is also hiring for full-time positions! Priority will be given to candidates who can start by the end of January 2027. Open positions: - (Senior) Research Scientist — Apply here: nvidia.wd5.myworkdayjobs.com… - (Senior) Research Engineer — Apply here: nvidia.wd5.myworkdayjobs.com… We work across #reasoning models, #generative simulation, #agentic #AI workflows, and #Physical AI #safety, with applications spanning autonomous vehicles and a broad range of Physical AI systems. If you’re interested in joining us, we’d love to hear from you! @NVIDIADRIVE @NVIDIARobotics @NVIDIAAI

It was a great week, really inspiring. And just fantastic to meet the students and other speakers!

One of the main weaknesses for each RL paradigm: the ego-policy adapts to whoever drives the other cars @MaxiIgl #ssad2026

Kashyap Chitta on the common task framework and the history of evaluation in ML and the value of benchmarks #ssad2026

The many trade-offs of setting the reward in RL for AD @MaxiIgl #ssad2026

Really enjoyed the summer school for autonomous driving today, lots of great questions and conversations! For anyone interested, my slides are online: maximilianigl.com/blog/rl-fo…

Today, we’re launching Alpamayo 2 Super, our frontier open reasoning model for autonomous vehicles. Beyond seeing, Alpamayo understands and reasons through the complex world - thinks before it acts. It’s a powerful backbone for robotaxis, trucks, shuttles, delivery vans, tractors and the long tail of mobile robots—billions of autonomous machines someday. We’re releasing it for commercial use under OpenMDW-1.1 so teams can inspect it, fine-tune it and deploy it—open models advance safety and security. The next wave of AI is robotics—and it starts with autonomous vehicles. Great work, Alpamayo team! blogs.nvidia.com/blog/alpama…

We just made it significantly easier to build your own reasoning-based AV. Alpamayo 2 Super: 32B params, 7+ cameras, 360° perception, chain-of-thought reasoning, and autolabeling. AlpaGym: closed-loop RL training so your model learns from its own mistakes in simulation. Full replay: nvda.ws/3Qkh2MG

🚗🏆 Breaking news: @nvidia #Alpamayo open platform has been named the winner of a COMPUTEX TAIPEI 2026 Best Choice Award in the Vehicle Technology & Smart Cockpit category, recognizing Alpamayo as one of the year’s major breakthroughs in automotive and Physical AI technology! Announcements: - blogs.nvidia.com/blog/nvidia… - bcaward.computex.biz/WinnerY… I’m incredibly proud of the team behind the Alpamayo open platform — Wenjie Luo @yan_wang_9 @iamborisi and the entire NVIDIA Autonomous Vehicle Research Group — and deeply grateful for the contributions from the NVIDIA AV production team Xinzhou Wu Sarah Tariq and many other researchers and developers across NVIDIA. This achievement was truly a collective team effort.👏 To get started with Alpamayo: — huggingface.co/blog/drmapavo… — huggingface.co/blog/drmapavo… And stay tuned — we’ll have several exciting announcements in the coming weeks. @NVIDIADRIVE @NVIDIAAI

Jensen today announced Alpamayo 1.5 at #NVIDIAGTC! #Alpamayo 1.5 is a major update to Alpamayo 1—@nvidia’s open 10B-parameter chain-of-thought reasoning VLA model, first introduced at #CES. Built on the #Cosmos-Reason2 VLM backbone and post-trained with RL, it adds support for navigation guidance, flexible multi-camera setups, configurable camera parameters, and user question answering. The result is an interactive, steerable reasoning engine for the AV community. We’re also releasing post-training scripts to help researchers and developers adapt the model. Additionally, we’ve significantly expanded the Alpamayo open platform across data and simulation, including releasing highly requested reasoning labels for the PhysicalAI Autonomous Vehicles dataset (huggingface.co/datasets/nvid…), as well as our chain-of-causation auto-labeling pipeline. 🔎 Learn more about Alpamayo 1.5 and the latest extensions to the Alpamayo open platform: huggingface.co/blog/drmapavo… (please note that most of the links will become active in the next few days.) Happy building—and stay tuned for more in the coming months! @NVIDIADRIVE @NVIDIAAI

Paper deadline for our "Simulation for Autonomous Driving" is in two days! The workshop is non-archival, so also submit your accepted (CVPR) papers!

Join me and my collaborators for a *live* discussion on @nvidia Alpamayo 1 (huggingface.co/nvidia/Alpama…), a reasoning-based vision–language–action (VLA) model for autonomous driving. 🎥 Livestream: Inside NVIDIA Alpamayo 1: Making Autonomous Vehicles Reason 🗓 February 11 ⏰ 9:00am PST 📍 Watch here: piped.video/watch?v=V9E4GX5v… As NVIDIA CEO Jensen Huang put it: “The ChatGPT moment for physical AI is here — when machines begin to understand, reason, and act in the real world. Robotaxis are among the first to benefit. Alpamayo brings reasoning to autonomous vehicles, allowing them to think through rare scenarios, drive safely in complex environments, and explain their driving decisions — it’s the foundation for safe, scalable autonomy.” During the livestream, we’ll cover: - How #reasoning-based #VLA models like #Alpamayo 1 are designed and built - Applications ranging from end-to-end #autonomy to reasoning-driven auto-labeling - Key opportunities and challenges in developing reasoning models for #Physical #AI I’ll be joined by core Alpamayo 1 developers @yan_wang_9 @YurongYou @wenhaoding95, and we’ll take questions live from the community. 📖 Ahead of time, you might enjoy this overview of the Alpamayo ecosystem: huggingface.co/blog/drmapavo… And if you’re attending @NVIDIAGTC (March 16–19) and would like to meet some of the Alpamayo team in person, you can use my employee code for 25% off your conference pass: nvidia.com/gtc/?ncid=GTC-NV1… Hope to see you at the livestream! @NVIDIAAI @NVIDIADRIVE

Simulation is essential for scaling the development of autonomous vehicles - from synthetic data generation to evaluation up to closed-loop training/reinforcement learning! We're organizing the Third Workshop on "Simulation for Autonomous Driving" (SAD) at #CVPR2026 in Denver, CO, USA, to bring together leading experts advancing simulation fidelity and simulation-based training. This half-day workshop features exciting keynotes from top researchers in the field, contributed papers, and a panel discussion - covering behavior modeling, sensor simulation, world models, reinforcement learning, and more. Invited Speakers: @drmapavone (Stanford / NVIDIA), @AnguelovDrago (Waymo), @francislee2020 (University of Hong Kong), Siva Manivasagam (Waabi), @wucathy (MIT). A big thank you to all speakers and organizers! Organizers: @yiyi_liao_, @MaxiIgl , Kashyap Chitta, @AzadehDinparast, Maximilian Naumann, @ZGojcic, @stan188249301, Kate Tolstaya, @wangjksjtu, @FidlerSanja, @shimon8282. 📝 Call for Papers is opening soon! Submission deadline: March 12, 2026. 🔗 agents4ad.github.io/

It’s incredibly exciting to see how quickly the community is engaging with the @nvidia Alpamayo ecosystem for developing reasoning-based autonomous vehicles (huggingface.co/blog/drmapavo…)! In this instance, TIER IV is showcasing Alpamayo 1’s reasoning capabilities in Tokyo, integrated with Autoware and ROS. Fantastic work, @ShinpeiKato and the @tier_iv_global team! 👏 Quick highlights about Alpamayo: Alpamayo 1: - Among HuggingFace’s top 10 overall trending models - Among the top 3 most downloaded models on HuggingFace when filtered by 'robotics' Alpamayo PhysicalAI–Autonomous-Vehicles dataset: - Trending in HuggingFace’s top 10 overall datasets Happy developing! 🚀 #AutonomousVehicles #Robotics #AI #Reasoning #HuggingFace #Autoware #ROS #AutonomousDriving #PhysicalAI #Alpamayo #RobotLearning @NVIDIAAI @NVIDIADRIVE

🚀 Exciting news from #CES2026! In his keynote today, Jensen announced @nvidia Alpamayo — a *fully open* ecosystem of models, simulation tools, and datasets designed to accelerate reasoning-based autonomous vehicle (AV) architectures and advance the path to Level 4 autonomous driving. Alpamayo brings together several technologies we’ve developed to enable reasoning-based vision–language–action (VLA) models for AVs. Our goal is to provide researchers and developers with a flexible, fast, and scalable platform for evaluating and training reasoning-based AV architectures in realistic closed-loop settings. Explore Alpamayo: -- Press Release: nvidianews.nvidia.com/news/a… -- Hugging Face Blog: huggingface.co/blog/drmapavo… -- Tech Blog: developer.nvidia.com/blog/bu… -- Alpamayo 1 reasoning model: research.nvidia.com/publicat… -- Physical AI AV Dataset: huggingface.co/datasets/nvid… -- AlpaSim simulator: github.com/NVlabs/alpasim I’m incredibly proud of the @nvidia AV Research team (research.nvidia.com/labs/avg…) and our many @nvidia collaborators whose contributions made this possible. More releases and features are coming soon — we can’t wait to see what the community builds with Alpamayo! 💡 Want to help grow the Alpamayo ecosystem? We’re hiring: [Sr.] Research Scientist: nvidia.wd5.myworkdayjobs.com… [Sr.] Research Engineer: nvidia.wd5.myworkdayjobs.com… #AutonomousVehicles #AutonomousDriving #AI #Simulation #ReasoningAI #OpenEcosystem #Alpamayo @NVIDIAAI @NVIDIADRIVE

🚗 Imitation learning is everywhere—but is it enough? So far, imitation learning—most commonly via behavior cloning (BC)—remains the go-to approach for training real-world autonomous vehicle (AV) driving policies. Yet BC operates in an open-loop (OL) fashion, overlooking the critical interdependence among inputs, outputs, and future states that comes with closed-loop (CL) operation. The result? The notorious—but often overlooked—OL–CL gap ⚠️ To address this challenge and encourage broader adoption of CL techniques, we’ve just published a survey (research.nvidia.com/publicat…) presenting a comprehensive taxonomy of closed-loop training methods for end-to-end driving. Our framework organizes approaches along three key axes: - Action generation - Environment response generation - Training objectives 💡 Bottom line: enabling technologies—like neural rendering, generative world models, and scalable RL—have now matured, making closed-loop AV training ready for wide-scale adoption. We’d love to hear your thoughts—drop a comment and join the discussion! 💬 And as a reminder, we are hiring for full-time research scientist and research engineer positions: 🔹 [Sr.] Research Scientist: nvidia.wd5.myworkdayjobs.com… 🔹 [Sr.] Research Engineer: nvidia.wd5.myworkdayjobs.com… @NVIDIADRIVE @NVIDIAAI @nvidia

We’ve just released the @nvidia Physical AI Autonomous Vehicles Dataset! huggingface.co/datasets/nvid… Highlights: - 1,727 hours of driving data collected by @nvidia - Spanning 25 countries and 2,500+ cities - Capturing diverse traffic, weather, and driving scenarios - Includes camera, LiDAR, and radar data This is just the beginning — features, tools, and challenges will continue to evolve. Stay tuned! @NVIDIADRIVE @NVIDIAAI

Saddened to hear about the recent Meta AI layoffs. We’re actively hiring for autonomous driving in NVIDIA Research. If you’ve researched large models, RL/simulation, or AI safety, we’d love to talk! 💚 nvidia.wd5.myworkdayjobs.com… nvidia.wd5.myworkdayjobs.com…

🚗🤖 Interested in reasoning models for embodied AI? I’m excited to share that at #NVIDIAGTC in DC I’ll unveil our latest work at #NVIDIA on reasoning Vision-Language-Action (VLA) models for vehicle autonomy: I’ll cover how we’re: • Advancing reasoning in VLA models • Powering a data flywheel for AV foundation models • Making autonomous driving more human-like and safer — with real-world driving videos! 🔗 Session info: nvda.ws/3IGfvwq 📍 Tuesday, Oct 28 • 3 PM Walter E. Washington Convention Center

We're looking for excellent interns in our AV research group at Nvidia for a broad range of topics: nvidia.wd5.myworkdayjobs.com… Applications from Europe are always possible for any listing, but we now have a dedicated listing as well, so please spread the word!