Peter Chen @peterxichen
Covariant CEO and Co-Founder. Previously @OpenAI, @UCBerkeley PhD. Joined December 2017-
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AI winter? No. Even if GPT-5 plateaus. Robotics hasn’t even started to scale yet. Embodied intelligence in the physical world will be a powerhouse for economic value. Friendly reminder to everyone that LLM is not all of AI. It is just one piece of a bigger puzzle.
AI winter? No. Even if GPT-5 plateaus. Robotics hasn’t even started to scale yet. Embodied intelligence in the physical world will be a powerhouse for economic value. Friendly reminder to everyone that LLM is not all of AI. It is just one piece of a bigger puzzle.
Synthetic data is the future! The advantage of synthetic data is the ability to control the data distribution, but not avoid real world data... you still require real world data to augment or train the generation engine.
Synthetic data is the future! The advantage of synthetic data is the ability to control the data distribution, but not avoid real world data... you still require real world data to augment or train the generation engine.
.@CovariantAI's RFM-1 model: The robot fails to suction grasp the socks. Then, thru internal dialogue, it devises a strategy of picking up the socks by the paper label. This adaptive behavior is hard to program with code, let alone scale it to more bots, objects & situations.
resonates with my own experience: robot demo --> INSANE PAIN --> robot creating value in production luckily I am hopeful we have by now paid most of our dues at Covariant :)
resonates with my own experience: robot demo --> INSANE PAIN --> robot creating value in production luckily I am hopeful we have by now paid most of our dues at Covariant :)
“We believe there will be a huge breadth of robotic form factors. Different types of hardware for different use cases— this all depends on frequency, speed, cost of installation, etc." - @peterxichen at @NVIDIAGTC
What makes the training data for RFM-1 unique? A few properties that are distinctive from typical lab data: 1. real-world complexity: picking from extremely cluttered scenes where item occlusion presents a challenge for reliability. 2. high-speed handling: the dynamics of…
What makes the training data for RFM-1 unique? A few properties that are distinctive from typical lab data: 1. real-world complexity: picking from extremely cluttered scenes where item occlusion presents a challenge for reliability. 2. high-speed handling: the dynamics of…
I often get asked "What's different about the current wave of #EGI - Embodied General Intelligence" 🟢 Agent making contacts, not avoiding them! There is a subtle but important nuance in what makes robotics hard, it's not the #contacts, it's the #contact_switches
Wednesday at @NVIDIAGTC: The impact of generative AI on robotics with @peterxichen and a panel of experts. Discover key insights on overcoming technical hurdles, seizing opportunities, and strategies for commercial success. nvidia.com/gtc/session-ca…
This is an amazing effort to collect more robotics data. I especially love that they have both structured data like multi-view stereo and more modern modality like text annotations. The key gap in robotics is data and it’s great to see the progress. Congrats @SashaKhazatsky
This is an amazing effort to collect more robotics data. I especially love that they have both structured data like multi-view stereo and more modern modality like text annotations. The key gap in robotics is data and it’s great to see the progress. Congrats @SashaKhazatsky
Infra behind RFM-1: Our Robotics Foundation Model is trained on several clouds; this gives us more GPUs for high experimentation velocity. Orchestration across clouds & serving entirely managed by @skypilot_org , lifting lots of infra burden off our team. More improvements soon!
We are unlikely to create an “ImageNet for Robotics”. In retrospect, ImageNet is such a homogeneous dataset. Labeled images w/ boxes. Generalist robot models will be fueled by the Data Pyramid, blending diverse data sources from web and synthetic data to real-world experiences.
Fully agree. There’s a lot of talk about *models*, but *data* access, governance, safety, attribution, multimodality, engineering, research and production is where the AI action is happening. More education on this is needed because it’s a big part of the safe and responsible…
Fully agree. There’s a lot of talk about *models*, but *data* access, governance, safety, attribution, multimodality, engineering, research and production is where the AI action is happening. More education on this is needed because it’s a big part of the safe and responsible…
Andrej Karpathy @karpathy
979K Followers 905 Following 🧑🍳. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets 🧠🤖💥
Jim Fan @DrJimFan
229K Followers 3K Following @NVIDIA Sr. Research Manager & Lead of Embodied AI (GEAR Lab). Creating foundation models for Humanoid Robots & Gaming. @Stanford Ph.D. @OpenAI's first intern.
Eric Jang @ericjang11
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Danijar Hafner @danijarh
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Animesh Garg @animesh_garg
21K Followers 1K Following Foundation Models for Generalizable Autonomy. Assistant Professor in AI Robotics @GeorgiaTech + @NvidiaAI. prev @Stanford @berkeley_ai @UofTCompSci
Shane Gu @shaneguML
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Rosanne Liu @savvyRL
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➕ SILVERSURFER.ETH .. @7SURFER7SILVER7
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Yann LeCun @ylecun
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aw~ Thanks <3 The current teleop process uses shared memory lock, which might not be necessary. Vuer is able to stream 2K Stereo Video at 60 fps when the Vuer thread is not being blocked by other things. See this opensource example: docs.vuer.ai/en/latest/exam…
Spent 4 hours setting up on my Vision Pro and palying around this. For 720P streaming, there is a 2~3s deplay. For lower resolution (376, 762), the delay is under 0.2s! I really love the vuer+VR experience! Great open-source by @xuxin_cheng @EpisodeYang and the team! Check…
"the only useful robot is a reliable robot"
Forbes asked me about Tesla’s claim they’ll sell humanoid robots to customers next year. My take: The only useful robot is a reliable robot. For humanoids to be ready for real work we can’t just be impressed by them, we need to be able to count on them. forbes.com/sites/robertha…
A peek on what are we working on lately for humanoid robot system. ☑️ Control bimanual hands from VisionPro real-time. ☑️An active camera is installed on the robot head, following human head motion, streaming ego-centric view observations in real time to VisionPro. Interfacing…
 🤖Introducing 📺𝗢𝗽𝗲𝗻-𝗧𝗲𝗹𝗲𝗩𝗶𝘀𝗶𝗼𝗻: a web-based teleoperation software!  🌐Open source, cross-platform (VisionPro & Quest) with real-time stereo vision feedback.  🕹️Easy-to-use hand, wrist, head pose streaming. Code: github.com/OpenTeleVision…
 🤖Introducing 📺𝗢𝗽𝗲𝗻-𝗧𝗲𝗹𝗲𝗩𝗶𝘀𝗶𝗼𝗻: a web-based teleoperation software!  🌐Open source, cross-platform (VisionPro & Quest) with real-time stereo vision feedback.  🕹️Easy-to-use hand, wrist, head pose streaming. Code: github.com/OpenTeleVision…
Our newest update demonstrates the Scaling Law in action, with RFM-1 now generating images at 400% higher resolution than previously. This higher resolution leads to more accurate AI predictions and fewer hallucinations. Check out RFM-1's enhanced ability to predict how a scene…
It has been one year since we announced GAIA-1 and six months since we shared our first scaled-up version. The diversity and realism of synthetic video from generative AI is still astounding to me... but now I'm getting excited about what we're seeing next...
@Thom_Wolf The 3 key elements of a good dataset: 1. quality 2. diversity 3. quantity You can only easily measure the last one but the performance is a sensitive function of all three. Super interesting topic ty for #longread :)!
Excited to announce we've raised 62.7M$ at 1.04B$ valuation, led by Daniel Gross, along with Stan Druckenmiller, NVIDIA, Jeff Bezos, Tobi Lutke, Garry Tan, Andrej Karpathy, Dylan Field, Elad Gil, Nat Friedman, IVP, NEA, Jakob Uszkoreit, Naval Ravikant, Brad Gerstner, and Lip-Bu…
We’re excited to announce that we’ve raised $62.7 million in a Series B1 funding led by Daniel Gross. The round also includes Stanley Druckenmiller, NVIDIA, Jeff Bezos, Tobi Lutke, Garry Tan, Andrej Karpathy, Dylan Field, Elad Gil, Nat Friedman, IVP, NEA, Jakob Uszkoreit, Naval…
AI winter? No. Even if GPT-5 plateaus. Robotics hasn’t even started to scale yet. Embodied intelligence in the physical world will be a powerhouse for economic value. Friendly reminder to everyone that LLM is not all of AI. It is just one piece of a bigger puzzle.
Zuck on Dwarkesh TLDR: AI winter is here. Zuck is a realist, and believes progress will be incremental from here on. No AGI for you in 2025. 1) Zuck is essentially an real world growth pessimist. He thinks the bottlenecks start appearing soon for energy and they will be take…
Maybe there are little flat spots along the way, but AI in 5 years will be ridiculously capable compared to AI today.
"This was too fun" Turn on volume to hear it. 🥰☺️🤗🤩 Follow to see what's next. #KindHumanoid #humanoid
Llama 3 is trained with over 10 Million human-annotated examples - that's also my guess of how many diverse trajectories you need to collect to get a generalist GPT for robotics after large-scale pretraining.
🔥llm.c update: Our single file of 2,000 ~clean lines of C/CUDA code now trains GPT-2 (124M) on GPU at speeds ~matching PyTorch (fp32, no flash attention) github.com/karpathy/llm.c… On my A100 I'm seeing 78ms/iter for llm.c and 80ms/iter for PyTorch. Keeping in mind this is fp32,…
Congrats to @AIatMeta on Llama 3 release!! 🎉 ai.meta.com/blog/meta-llam… Notes: Releasing 8B and 70B (both base and finetuned) models, strong-performing in their model class (but we'll see when the rankings come in @ @lmsysorg :)) 400B is still training, but already encroaching…
Jensen attended the AI forum at Oregon State University on Sunday, where he was asked about his vision for humanoid robots. He described the "Aha!" moment that convinced him of the potential for generalized robotics.
We promise this is not a person in a bodysuit. bit.ly/3w5XRvH
This video is a first look at Lingo-2, an AI simultaneously chatting and autonomously driving through busy central London. This is not a LLM strapped to our driving AI, rather an AI model jointly trained on vision, language and action. 💬🚗
🚙💬Meet Lingo-2, a groundbreaking AI model that navigates roads and narrates its journey. Watch this video taken from a LINGO-2 drive through Central London 🇬🇧 The same deep learning model generates real-time driving commentary and drives the car.
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!
research is an immensely taxing endeavour. hours spend doing IC work, debugging and what not. a paper is a canvas for researchers to express themselves after all the hard work, at the end of the day. it's my art. at least let me paint the way i want to paint. The reason why i am…
In retrospect, UL2 was a wild paper. «Yeah so this just sort of cooked, turns out it's more optimal than Chinchilla, idk check it out». This almost farcically casual tone makes me suspect that Yi was thinking in detail about founding Reka at the moment. arxiv.org/abs/2205.05131
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