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E-Atlas is finally out. And I love the design so much. Better RoM, torque density, and form factor than any robot I've seen in a while. I'll be adding thoughts in this thread. youtu.be/29ECwExc-_M?si…
An awesome and refreshing benchmark by Carlo and collaborators featuring practically useful tasks like truck unloading. All open-source, built on MuJoCo and accelerated with JAX!
An awesome and refreshing benchmark by Carlo and collaborators featuring practically useful tasks like truck unloading. All open-source, built on MuJoCo and accelerated with JAX!
Mind blown by these results and of course the insane amount of meticulous work that went into it!
Mind blown by these results and of course the insane amount of meticulous work that went into it!
Some fine educational material and useful, fun-to-read code to satisfy your nonlinear least-squares needs. Check out the new tutorial colab from the MuJoCo team github.com/google-deepmin… Channeling my inner @RussTedrake 🧑🏫
Finally got around to port this over to MuJoCo!
Finally got around to port this over to MuJoCo! https://t.co/UesWcaDEAf
Can we leverage VLMs for robot manipulation in the open world? Checkout our new work MOKA, a simple and effective visual prompting method!
What state representation should robots have? 🤖 I’m thrilled to present an Any-point Trajectory Model (ATM), which models physical motions from videos without additional assumptions and shows significant positive transfer from cross-embodiment human and robot videos! 🧵👇
"pov footage of an ant navigating the inside of an ant nest" Video generated by Sora
I've updated the tutorial MuJoCo controller library with 3 examples on 3 different robots: github.com/kevinzakka/mjc…
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)
Led by @GoogleDeepMind, we present ALOHA 2 🤙: An Enhanced Low-Cost Hardware for Bimanual Teleoperation. ALOHA 2 🤙 significantly improves the durability of the original ALOHA 🏖️, enabling fleet-scale data collection on more complex tasks. As usual, everything is open-sourced!
Before diving into the hardware, we also release a *proper* ALOHA sim model with SysID, thanks to @kevin_zakka @the_real_btaba @ayzwah. Even if you don’t have the hardware, there is now a way to perform complex tasks with ALOHA in Mujoco!
Introducing TEXterity ~ our method for simultaneous tactile estimation and control for extrinsic dexterity 👉TEXterity tackles precise in-hand manipulation with simple grippers, for tasks like assembly and tool-use 🍎website (videos + paper) : sites.google.com/view/texterity 🧵👇
L take. BD was doing the impossible for a few years and pushing the state-of-the-art on many fronts. Now all of a sudden what they did was gimmicky because a few startups started doing teleop and "re-invented" 2015 results to the public eye.
L take. BD was doing the impossible for a few years and pushing the state-of-the-art on many fronts. Now all of a sudden what they did was gimmicky because a few startups started doing teleop and "re-invented" 2015 results to the public eye.
Witnessed a few training runs in person, the learning speed was extremely impressive!
Witnessed a few training runs in person, the learning speed was extremely impressive!
MuJoCo 3.0 has gotten significantly better at simulating deformable materials and it beats NVIDIA Flex and other simulators in this project. Congrats @TheSmallQuail !!
MuJoCo 3.0 has gotten significantly better at simulating deformable materials and it beats NVIDIA Flex and other simulators in this project. Congrats @TheSmallQuail !!
Our recommendation? @GoogleDeepMind MuJoCo. After the update to version 3 the simulation of deformable objects has significantly improved! It closely matches the groundtruth on both dynamic (left) and quasi-static (right) tasks and allows importing cloth meshes.
Super excited to announce our new work: Synthesizing Moving People with 3D Control (3DHM)💡 Why is 3DHM unique? With 3D Control, 3DHM can animate a 𝗿𝗮𝗻𝗱𝗼𝗺 human photo with 𝗮𝗻𝘆 poses in a 𝟯𝟲𝟬-𝗱𝗲𝗴𝗿𝗲𝗲 camera view and 𝗮𝗻𝘆 camera azimuths from 𝗮𝗻𝘆 video!
Eric Jang @ericjang11
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21 Followers 438 Following Strong passion for AI and Interested in how computer chips (AI acclerators) works.Jindong Gu @Jindong73504766
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457 Followers 5K FollowingMark Kovarski @mkovarski
2K Followers 5K Following Responsible AI, Cloud, SaaS, Product 🤖 🫶🌐💡 | https://t.co/2vuiFosXlm 📪Eric Jang @ericjang11
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185K Followers 871 Following Cofounded and lead @PyTorch at Meta. Also dabble in robotics at NYU. AI is delicious when it is accessible and open-source.Alfredo Canziani @alfcnz
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28K Followers 1K Following Research Scientist & Manager @GoogleDeepMind Tokyo/MTV. ex: @GoogleAI Brain, @OpenAI. (JP: @shanegJP)Ted Xiao @xiao_ted
11K Followers 678 Following I teach robots to be smarter @GoogleDeepMind. Tweets about robot learning, scaling, and large models. Opinions my own.Jia-Bin Huang @jbhuang0604
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23K Followers 445 Following Working at the intersection of ML and Systems @ PyTorch "My learning style is Horace twitter threads" - @typedfemaleDanijar Hafner @danijarh
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34K Followers 607 Following Researching reasoning @OpenAI | Co-created Libratus/Pluribus, the first superhuman no-limit poker AIs | Co-created CICERO | PhD from @SCSatCMUNathan Lambert @natolambert
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18 Followers 27 FollowingNathan Peterman @NathanTylerP
591 Followers 912 Following Follow if you like bad jokes and robots, but mostly robots (he/him) Former Agility Robotics, NASA JSC, Purdue. Looking forward to the next robotic adventureMichael Lutter @_mlutter
983 Followers 262 Following Researching Robot Reinforcement Learning @BostonDynamics 🤖🧠 . Prev: @DeepMind, @NVIDIAAI, @ias_tudarmstadt & @TU_MuenchenJacob Austin @jacobaustin132
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288 Followers 257 Following I am a doctoral student at @ETH_en and researcher of @ComputationalR2. My research aims to generate more animal-like walking motions of legged robots.Yide Shentu @YideShentu
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88 Followers 223 Following Computer Science PhD student @UCBerkeley BAIR @Berkeley_AI. Make Robots Work.Can't believe a some random startup (Boston Dynamics? Never heard of it) would blatantly rip off designs from long-time industry leaders like Figure
Won’t be the last time we get copied If it’s not obvious yet, Figure is doing the best mechanical design in the world for robotics Let us cook
E-Atlas is finally out. And I love the design so much. Better RoM, torque density, and form factor than any robot I've seen in a while. I'll be adding thoughts in this thread. youtu.be/29ECwExc-_M?si…
Quick personal update-- Excited to share that I’ll be joining @Berkeley_EECS to start a PhD this autumn. Looking forward to start working w/ @JitendraMalikCV & @pabbeel! 🤖
Introducing my recent collaboration work, "Spatio-Temporal Motion Retargeting for Quadruped Robots" co-authored with Taerim Yoon, Seungmin Kim, Minsung Ahn, Stelian Coros, and Sungjoon Choi. terry97-guel.github.io/STMR-RL.github…
You all can look forward to a **even faster** ManiSkill 3 (official v3 coming out hopefully in may/june). Many many things are GPU parallelized, far more than Isaac. Also, it's a single pip install and ManiSkill 3 remains still a single pip install + runnable on Colab 😁
I like this advice. If I was getting started as a robotics student these days, I think I would install ManiSkill2 and try to get some learning stuff working - I like that it has great simulations of "real" robot sensors, is fast, and easy to start with.
We promise this is not a person in a bodysuit. bit.ly/3w5XRvH
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!
For the past year we've been working on ALOHA Unleashed 🌋 @GoogleDeepMind - pushing the scale and dexterity of tasks on our ALOHA 2 fleet. Here is a thread with some of the coolest videos! The first task is hanging a shirt on a hanger (autonomous 1x)
Current progress: It has a stepper motor now and it can be controlled by an Arduino.
Progressively getting rid of randomness in your training pipelines is one of the most enjoyable things. Determinism is king.
Had a chance to visit the University of Edinburgh and see some cool robots and meet some researchers. Thanks to @peterdavidfagan for making this happen!
Suzume! 🪑
『すずめの戸締まり』に登場する3本脚の椅子を再現したロボット設計,強化学習による歩容生成の論文を公開しました! 来週アメリカで開催されるRoboSoft2024にて発表します! website - shin0805.github.io/chair-type-tri… #すずめの戸締まり
Craftsmanship, Steve Jobs.
This is exactly what I hate with all big frameworks. TF is terrible. PyTorch used to be straightforward but turned terrible too. Torch7 was very direct. JAX/Flax still ok, but I pray every day that it doesn’t end up with the same fate over time.
Have you ever wanted to train LLMs in pure C without 245MB of PyTorch and 107MB of cPython? No? Well now you can! With llm.c: github.com/karpathy/llm.c To start, implements GPT-2 training on CPU/fp32 in only ~1,000 lines of clean code. It compiles and runs instantly, and exactly…
Lost my Thesaurus. Gutted. Really gutted. Like absolutely gutted.
a self-balancing holonomic robot from niche robot youtube
Andrej frickin' Karpathy man. Living the life all us ML nerds want to live.
New side quest unlocked: Just soldered my first components to a PCB and have to admit it’s not that much different from wound cauterization
Have you ever wanted to train LLMs in pure C without 245MB of PyTorch and 107MB of cPython? No? Well now you can! With llm.c: github.com/karpathy/llm.c To start, implements GPT-2 training on CPU/fp32 in only ~1,000 lines of clean code. It compiles and runs instantly, and exactly…