Suraj Nair @SurajNair_1
Building robot foundation models at Physical Intelligence. surajnair.com Palo Alto, CA Joined September 2019-
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Super excited that the DROID dataset is out -- huge shoutout to the whole team especially leads @SashaKhazatsky and @KarlPertsch! Can't wait to see what the community can build with this dataset 🤖
Super excited that the DROID dataset is out -- huge shoutout to the whole team especially leads @SashaKhazatsky and @KarlPertsch! Can't wait to see what the community can build with this dataset 🤖
Since cat is out of the bag, it’s time I share: I’ll be starting a new adventure with an incredible team of friends and long-time collaborators to take on the big challenge of robot learning at scale! It's called Physical Intelligence (Pi… or π, like the symbol). 🧵👇
I’m most excited about our team – @brian_ichter, @svlevine, @hausman_k, @lachygroom, @QuanVng, @SurajNair_1, + a few other amazing people to be shared soon. If you’re interested in joining us, please get in touch! [email protected]
Thrilled to be starting a new adventure at Physical Intelligence with some amazing colleagues and friends! Learn more: physicalintelligence.company
Thrilled to be starting a new adventure at Physical Intelligence with some amazing colleagues and friends! Learn more: physicalintelligence.company
Can we collect robot data without any robots? Introducing Universal Manipulation Interface (UMI) An open-source $400 system from @Stanford designed to democratize robot data collection 0 teleop -> autonomously wash dishes (precise), toss (dynamic), and fold clothes (bimanual)
I'm on the faculty market! My goal is to build language systems that we understand deeply through discovery and by design, so we can precisely control them and treat their failures. Let's tackle this grand challenge of science and engineering together. nlp.stanford.edu/~johnhew/
Incredibly honored that Voltron is one of the nominees for Best Paper at #RSS2023! Just landed in Daegu, South Korea and can’t wait to present on Tuesday (catch our talk in Session 4 at 3 PM KST). Excited to meet everyone, and stoked for a week of awesome talks and demos!
Incredibly honored that Voltron is one of the nominees for Best Paper at #RSS2023! Just landed in Daegu, South Korea and can’t wait to present on Tuesday (catch our talk in Session 4 at 3 PM KST). Excited to meet everyone, and stoked for a week of awesome talks and demos!
1/ How do humans and animals form models of their world? We find that Foundation Models for Embodied AI may provide a framework towards understanding our own “mental simulations”. 🧵👇 arxiv.org/abs/2305.11772 with awesome collaborators: @rishi_raj @mjaz_jazlab @GuangyuRobert
#PhDone! Defended my thesis this past week, wrapping up 5 wonderful years at @Stanford! I’d like to thank my co-advisors (@dntse, @SalzmanLab), collaborators, friends, and family. I could not have done this without you. 1/4
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Want a really simple (and cheap!) way to improve neural net calibration and get practical epistemic uncertainty estimates? At ICLR this year: Variational Bayesian Last Layers Try it out: 1. pip install vbll 2. a couple one line changes to your current training pipeline 🧵
Introducing 𝐀𝐋𝐎𝐇𝐀 𝐔𝐧𝐥𝐞𝐚𝐬𝐡𝐞𝐝 🌋 - Pushing the boundaries of dexterity with low-cost robots and AI. @GoogleDeepMind Finally got to share some videos after a few months. Robots are fully autonomous filmed in one continuous shot. Enjoy!
Some personal news: I’m excited to be joining Hello Robot, to lead their Embodied AI effort! For years now, I’ve been a passionate supporter of their vision of affordable, useful robots that can help people out with their day-to-day lives. I’ve previously worked at FAIR, part of…
@ashleevance Thanks for the kind words, @ashleevance! It's certainly hard to find an opportunity that properly follows our incredible journey at @anduriltech, but co-founding @physical_int with this team is something truly special. Can't wait for you to see what we have in store!
Physical Intelligence is really going for it. Just saw Adnan pop up on their web site. Former Tesla and Anduril exec and one of the smartest humans I have ever met, and I get paid to meet smart humans
At TRI, we are looking to build Robotics Foundation Models, or what we call Large Behavior Models (LBMs). Large scale robotics datasets, such as DROID are a part of the strategy to enable broadly capable LBMs that include language, vision and action: droid-dataset.github.io…
Introducing a new, fully open robotics dataset! - 76k episodes - 564 unique scenes - 100 contributors - 13 labs/institutions - 3 continents droid-dataset.github.io A short 🧵 on the backstory
Check out PRIME, our work on making imitation learning algorithms significantly more data-efficient! Inspired by how humans imitate, PRIME parses demonstrations into a high-level sequence of semantically meaningful skills. Work led by @TianGao_19 👇
Imitation learning often involves significant human effort to collect a large dataset for robust policy learning. How can we train robust policies in low-data regimes? Our imitation learning framework PRIME scaffolds manipulation tasks with behavior primitives, breaking down…
Introducing Yell At Your Robot (YAY Robot!) 🗣️- a fun collaboration b/w @Stanford and @UCBerkeley 🤖 We enable robots to improve on-the-fly from language corrections: robots rapidly adapt in real-time and continuously improve from human verbal feedback. YAY Robot enables…
After two years, it is my pleasure to introduce “DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset” DROID is the most diverse robotic interaction dataset ever released, including 385 hours of data collected across 564 diverse scenes in real-world households and offices
Excited to announce that with a few incredible folks, we're starting a company -- Physical Intelligence (Pi, π, @physical_int). We're focused on bringing the amazing recent breakthroughs of AI and foundation models into the physical world.
I’m really excited to be starting a new adventure with multiple amazing friends & colleagues. Our company is called Physical Intelligence (Pi or π, like the policy). A short thread 🧵
Since cat is out of the bag, it’s time I share: I’ll be starting a new adventure with an incredible team of friends and long-time collaborators to take on the big challenge of robot learning at scale! It's called Physical Intelligence (Pi… or π, like the symbol). 🧵👇
I’m most excited about our team – @brian_ichter, @svlevine, @hausman_k, @lachygroom, @QuanVng, @SurajNair_1, + a few other amazing people to be shared soon. If you’re interested in joining us, please get in touch! [email protected]
🚨 Big news 🚨 Together with a set of amazing folks we decided to start a company that tackles one of the hardest and most impactful problems - Physical Intelligence In fact, we even named our company after that: physicalintelligence.company or Pi (π) for short 🧵
Some personal updates! Excited to join the team @Figure_robot to help building AI for the robot age! 🤖
Super excited for new adventures with @faunarobotics! Stay tuned!
At Fauna Robotics, we are creating a world where human and robotic fauna coexist, collaborate, and flourish together. 🌿🤖 Our founding team has deep backgrounds in robotics, shipping products, and company building. We're hiring across research, design, and eng roles in NYC.
Big personal news: after 7 wonderful years leading ML at TRI (@ToyotaResearch), I'm thrilled to be joining the early-stage deep tech VC firm Calibrate Ventures (@CalibrateVC) as a Partner! I will stay involved at Stanford as a professor and at TRI as an advisor, as there is still…
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