Exciting news from former Stanford ASL member Ramon Dario Iglesias 🌐 Check out his new company Clementine!

One more company being started this week by a Stanford ASL alumn, Brian Ichter, together with great colleagues!

Excited to announce our workshop "Structural Priors as Inductive Biases for Learning Robot Dynamics" at the upcoming #RSS2024 conference! Submit your papers/poster abstracts by June 1!  sites.google.com/alora.tech/pri… Stanford ASL

Yesterday we officially launched CAESAR: the Stanford Center for AEroSpace Autonomy Research: caesar.stanford.edu. Goal: solve the hard problems in spacecraft autonomy through the judicious incorporation of AI. More here: spacenews.com/stanford-cente… Stanford Engineering Stanford AI Lab

At #CVPR2024 we will be presenting LLaDa, an #LLM-based driving assistant that, among other things, can help people with driving in unfamiliar places. Great work led by Boyi Li! NVIDIA DRIVE NVIDIA AI

Online map estimation is a key task in modern autonomy stacks. In our upcoming (and award candidate!) #CVPR2024 paper we show how to do so reliably by carefully leveraging uncertainty information. Great collaboration with Boris Ivanovic and Igor Gilitschenski's group.

If you are #CVPR2024, consider attending our workshop on "Vision and Language for Autonomous Driving and Robotics" with an amazing lineup of speakers! Details here: vision-language-adr.github.io

Can we use NeRFs in the wild? Introducing DistillNeRF, a framework for *generalizable* 3D scene representation prediction from sparse multiview image inputs, using distillation from per-scene optimized NeRFs and visual foundation models. arxiv.org/pdf/2406.12095 NVIDIA AI

How can we best use LLMs in an autonomy stack? An exciting prospect is to exploit their generalist experience to reason about anomalies. And one can do this in real time by leveraging their embeddings in a fast&slow decision making architecture. Work led by Rohan Sinha #RSS2024

I am excited to share that our paper: "Real-Time Anomaly Detection and Reactive Planning with Large Language Models” has received the best paper award at #RSS2024! Paper: arxiv.org/pdf/2407.08735… Project website: sites.google.com/view/aesop-llm Stanford Engineering NVIDIA AI #Robotics

As AI is implemented in our daily lives, engaging with #robots and autonomous vehicles safely will become more important. RSS’s 🏆 best paper from Stanford AI Lab and NVIDIA AI Developer presents a framework designed to improve the trustworthiness of dynamic robotic systems under

Check out VILA^2: VILA Augmented VILA. VILA^2 leverages self-augmentation to achieve new SOTA for vision language models (VLMs). Such powerful VLM models will be key to advance the state of the art in AV and robotics. Paper: arxiv.org/abs/2407.17453 NVIDIA AI

The new Italian Foundation on Artificial Intelligence for Industry (AI4I) is looking for a Director! A unique opportunity to shape the R&D AI agenda in Italy and in Europe (I serve as member of the scientific committee). Apply here: ai4i.it/call-for-direc… Fabio Pammolli #AI

Our work on leveraging Large Language Models (LLMs) as cognitive agents for autonomous driving (Agent-Driver) has been accepted to Conference on Language Modeling with top 1% reviews! Paper: arxiv.org/pdf/2311.10813 Great work led by Yue Wang

Video captioning is nowadays a critical tool to fuel data flywheels for AV and robot development. We have just released Wolf: a novel video captioning framework achieving SOTA in a number of settings: Paper: arxiv.org/pdf/2407.18908 Related challenge: wolfv0.github.io/leaderboard.ht…

Consider submitting your work to this exciting European Conference on Computer Vision #ECCV2024 workshop: "Autonomous Vehicles meet Multimodal Foundation Models" Bonus: you get to visit Italy ;) Website: mllmav.github.io Deadline: August 15

@Ai4I The call for the Founding Director position is open! Spread the word! nature.com/naturecareers/… Ali Jadbabaie Lex Fridman Yann LeCun Markus Gross MIT CSAIL MIT IDSS Marco Pavone ISSNAF Vector Institute The Alan Turing Institute

The #RSS2024 Outstanding Paper Award: "Real-Time Anomaly Detection and Reactive Planning with Large Language Models" by R Sinha, A Elhafsi, C Agia, M Foutter, E Schmerling, M Pavone #robotics #research #awards You can see a list of all finalists here: roboticsconference.org/program/awards/