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The Autonomous Vehicle (AV) Research Group @NVIDIAAI is looking for talented interns! Dive into cutting-edge work—from reasoning models and generative simulation to AI safety—and help shape the future of AV and embodied AI. Ready to push the limits? Apply now:…
Are you a PhD student excited to build the future of Autonomous Vehicles? The @nvidia Autonomous Vehicles Research Group is now recruiting PhD research interns for 2026!! Apply here: nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAEx…
We’re now accepting applications for the 2026–2027 NVIDIA Graduate Fellowships! If you’re passionate about advancing cutting-edge reasoning models for Physical AI applications 🚗🤖, apply here: research.nvidia.com/graduate-fello… — and be sure to select “Autonomous Vehicles.” @NVIDIAAI
Can we use simulation to validate Physical AI? Yes—with far fewer real-world tests. We propose a control variates–based estimation framework that pairs sim & real data to dramatically cut validation costs. #AI #Robotics #Sim2Real" Paper: arxiv.org/pdf/2506.20553 @NVIDIADRIVE
Happy to share our latest work on efficient sensor tokenization for end-to-end driving architectures! arxiv.org/abs/2506.12251 We introduce a novel way to tokenize multi-camera input for AV Transformers that is resolution- and camera-count-agnostic, yet geometry-aware 🧵👇
Our @CVPR paper on training traffic models in closed loop is an Oral at CVPR!! The work was done by Zhejun Zhang (zhejz.github.io) in collaboration with @KarkusPeter, me, @wenhaoding95, @Yuxiao_Chen_, @iamborisi and @drmapavone. Page: zhejz.github.io/catk/ 🧵...
Don’t miss this deep dive into the future of autonomous vehicles! Excited to present about how foundation models are transforming AV technology with @ALVAREZ_JOSEM at #GTC25! Check out all the session details below 👇
💡 Learn about leveraging foundation models such as vision-language models and video generation models for #autonomousvehicle development in this new #GTC25 session on Mar. 19, 4pm: Research to Production: Transforming AV Technology With AI [S72707] ➡️ nvda.ws/4kDXr49
![NVIDIADRIVE's tweet image. 💡 Learn about leveraging foundation models such as vision-language models and video generation models for #autonomousvehicle development in this new #GTC25 session on Mar. 19, 4pm:
Research to Production: Transforming AV Technology With AI [S72707]
➡️ nvda.ws/4kDXr49](https://pbs.twimg.com/media/Glz68AyXwAAZhqC.jpg)
For the first time ever, @nvidia is hosting an AV Safety Day at GTC - a multi-session workshop on AV safety. We will share our latest work on safe AV platforms, run-time monitoring, safety data flywheels, and more! #AutonomousVehicles #AI at #GTC25 ➡️ nvda.ws/3Xc3xPo
Want a haptic force feedback glove? Meet DOGlove! 🖐✨ A precise, low-cost (~$600), open-source glove for dexterous manipulation. Teleoperate a dexterous hand to squeeze condensed milk on bread 🥪 or collect high-quality data for imitation learning. Check it out! 🎥👇…
AI4I, the Italian Institute of Artificial Intelligence for Industry (ai4i.it), has launched an international call for Heads of R&D Units (ai4i.it/call-for-head-…). This is a unique opportunity to shape the AI roadmap in Italy and beyond! @FabioPammolli
Complementing DreamDrive, I am thrilled to introduce STORM, which enables fast scene reconstruction with a single feed-forward model. STORM transforms camera logs into dynamic 3D models - in real time! Web: jiawei-yang.github.io/STORM/ Paper: arxiv.org/abs/2501.00602
Introducing DreamDrive, which combines the complementary strengths of generative AI (video diffusion) and neural reconstruction (Gaussian splatting) to transform any street-view image into a dynamic 4D driving scene! Web: pointscoder.github.io/DreamDrive/ Paper: arxiv.org/abs/2501.00601
🔍 Inference-time scaling is a key focus in foundation models, but its origins trace back to model-based RL (MBRL). In MBRL, a critical challenge arises from reconciling the conflict between "world model prediction" and "task reward"—the gap between next-state prediction accuracy…
[1/4] 🌟Sneak Peek: SPARK in Action! 🦾 Previewing Safe Protective & Assistive Robot Kit (SPARK)—a modular toolbox designed to enhance safety in humanoid autonomy and teleoperation. Safety isn't just a feature—it's the foundation for humanoids to truly integrate into human life.…
We also have openings for interns. The link is nvidia.wd5.myworkdayjobs.com/NVIDIAExternal…
The Autonomous Vehicle (AV) Research group @nvidia is now hiring. From AV foundation models to AI safety and generative simulation, we are pushing the state of the art in AV and embodied AI! To apply: Junior RS: nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAEx… Senior RS: nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAEx…
What a pity to miss a wonderful in-person IROS conference! Don’t forget to check our RAL paper: ieeexplore.ieee.org/stamp/stamp.js… and our project page! Code base: github.com/HenryLHH/fusion Project page: sites.google.com/view/safe-fusi…
How can we enhance the reasoning capabilities for RL agents? We present FUSION, a causality-guided trustworthy reinforcement learning framework that can achieve satisfactory performance in safety-critical domains like autonomous vehicle agents under distribution shift. #ML4AD
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