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100,000 hours of human hands doing real work. LeRobot format, fully annotated and open. EgoSuite-Open100K from Lightwheel X Hugging Face: 15,000+ tasks across 15,000+ real scenes, hand + body pose and wrist cams. Recorded across 7 environment categories and 128 scene types, from kitchens and bedrooms to warehouse floors... show more

LeRobot

20,693 subscribers

45,647 次观看 • 1 个月前 •via X (Twitter)

科学技术教育健康养生

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24 条评论

Yechan Do 的头像

Yechan Do1 个月前

@LightwheelAI @huggingface Dataset which was the bottleneck is solving!

Konstantin Saifoulline 的头像

Konstantin Saifoulline1 个月前

@LightwheelAI @huggingface Why vibecoding a video like this looks super cheap. Congrats doe

Pawel 的头像

Pawel1 个月前

@LightwheelAI @huggingface Could we possibly use Meta Quest for this?

Heidy Daumas 的头像

Heidy Daumas1 个月前

@LightwheelAI @huggingface Oh Damn

Sani Ai Tech 的头像

Sani Ai Tech1 个月前

@LightwheelAI @huggingface Open datasets at this scale can seriously accelerate embodied AI research

Eugene Mironov 的头像

Eugene Mironov1 个月前

@LightwheelAI @huggingface Very cool 🔥

ZenithAi 的头像

ZenithAi1 个月前

@LightwheelAI @huggingface An impressive open dataset for advancing real-world robotics research.

Aina Ai | Tools & Updates 的头像

Aina Ai | Tools & Updates1 个月前

100K hours of real human work open and annotated EgoSuite Open100K is a massive win for robotics

Dhruv 的头像

Dhruv1 个月前

@LightwheelAI @huggingface Interesting

Ella Tech & Tool 的头像

Ella Tech & Tool1 个月前

@LightwheelAI @huggingface 100K hours open?! Huge win for robotics

AI Mastery Guide 的头像

AI Mastery Guide1 个月前

@LightwheelAI @huggingface 100k hours of data, huge for robotics

IIIΞ FUGARU 的头像

IIIΞ FUGARU1 个月前

@LightwheelAI @huggingface At first I thought it was some Mistral release or something🤭

Crypto With Ayla 的头像

Crypto With Ayla1 个月前

@LightwheelAI @huggingface A 100K-hour open dataset at this scale could be a major resource for advancing real-world embodied AI and robotics research. 🤖🔥📊

Elara AI 的头像

Elara AI1 个月前

@LightwheelAI @huggingface 100000 hours of human hands open data for robotics

Aria Tech 的头像

Aria Tech1 个月前

@LightwheelAI @huggingface 100k hours of real hand data open for everyone is huge

Elise Tech Ai 的头像

Elise Tech Ai1 个月前

@LightwheelAI @huggingface Absolutely massive for open robotics! Open datasets like this will accelerate the next wave of embodied AI.

Phoenix 的头像

Phoenix1 个月前

@LightwheelAI @huggingface @LeRobotHF is on fire, honestly

Olibea 的头像

Olibea1 个月前

@LightwheelAI @huggingface Domain available for sale

Aria Tech 的头像

Aria Tech1 个月前

@LightwheelAI @huggingface Massive dataset and open access will accelerate robotics research

Evia AI 的头像

Evia AI1 个月前

@LightwheelAI @huggingface Open datasets at this scale could seriously accelerate embodied AI

Kosi.py 的头像

Kosi.py1 个月前

@LightwheelAI @huggingface 100k ? Literally?

Olibea 的头像

Olibea1 个月前

@LightwheelAI @huggingface Domain and available for sale

Steven Cheng 的头像

Steven Cheng1 个月前

@LightwheelAI @huggingface Finally, data that understands the chaos of real kitchens.

Vantix AI Agency 的头像

Vantix AI Agency1 个月前

@LightwheelAI @huggingface 100K hours of real world hand work open massive gift to robotics

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The largest fully annotated open egocentric human dataset. Today we're open-sourcing EgoSuite-Open100K with Hugging Face : 100,000 hours of egocentric human data, free for anyone to use. Physical AI has a scaling law of its own now, and its input is human data. That part is settled. What the field still needs is a shared foundation to build on. 15,000+ tasks. 15,000+ real scenes, from factory floors to retail backrooms. Hand pose, body pose and subtask-level semantics, with wrist camera coverage on part of the set. Licensed for commercial training, not research-only. We build the data infrastructure for Physical AI. Open100K is the first public layer of it. The first 10,000 hours are live now, with the rest rolling out in stages.

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Lightwheel

75,420 次观看 • 1 个月前

Robotics has a data problem, and egocentric data is a compelling way to solve it because egocentric data is (1) scalable — it’s cheap to collect — and (2) easily captures the breadth and diversity of real human tasks, while (3) being true to real physics. Lightwheel recently released a hundred thousand hours of high-quality egocentric video data, spread across a wide range of human tasks from cleaning and tidying to assembly and construction to retail tasks. Here to tell us about this tremendous effort is Steve Xie, CEO and co-founder of Lightwheel. The data is also available on HuggingFace right now. Watch Episode 102 of RoboPapers, with Michael Cho - Rbt/Acc and Jiafei Duan, to learn more!

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RoboPapers

33,675 次观看 • 1 个月前

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Lukas Ziegler

40,583 次观看 • 6 个月前

Nvidia is now a humanoid robot designer. That's the real takeaway from this news. Nvidia is acquiring Hugging Face for $12.93B. Hugging Face is the largest open-model and dataset hub, the "GitHub of AI," with 3M+ models and 18M+ developers, robotics included. But here's the interesting part: Hugging Face has a serious robotics team from its acquisition of Pollen Robotics, which designs and builds open-source hardware platforms for robots, including humanoids (Reachy). Pollen team now gets the backing of the world's most valuable company. $NVDA

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10,755 次观看 • 1 个月前

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24,133 次观看 • 1 年前

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Over the Reality 🌐

34,785 次观看 • 1 个月前

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Atul Kumar

79,465 次观看 • 13 天前

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244,598 次观看 • 1 个月前

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114,335 次观看 • 1 年前

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Ilir Aliu

13,264 次观看 • 3 个月前

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LeRobot

13,451 次观看 • 2 个月前

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156,386 次观看 • 2 年前

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Paul Liang

49,323 次观看 • 6 个月前

What happens when robot world models learn from human experience at scale? 🤔 DreamDojo from NVIDIA Research is a generalist robot world model pretrained on 44K hours of egocentric human videos and then post-trained on robot data to generalize across new objects and environments. After distillation, it runs at 10 FPS for live teleoperation, policy evaluation, and model-based planning. Read the ICML paper to learn more 📄

What happens when robot world models learn from human experience at scale? 🤔 DreamDojo from NVIDIA Research is a generalist robot world model pretrained on 44K hours of egocentric human videos and then post-trained on robot data to generalize across new objects and environments. After distillation, it runs at 10 FPS for live teleoperation, policy evaluation, and model-based planning. Read the ICML paper to learn more 📄

NVIDIA Robotics

23,392 次观看 • 3 个月前

Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

20,457 次观看 • 4 个月前

We previously shared our research on Layer Skip, an end-to-end solution for accelerating LLMs from researchers at Meta FAIR. It achieves this by executing a subset of an LLM’s layers and utilizing subsequent layers for verification and correction. We’re now releasing inference code and fine-tuned checkpoints for this work. Model weights on Hugging Face ➡️ More details ➡️ We hope that releasing this work will open up new areas of experimentation and innovative new research in optimization and interpretability.

We previously shared our research on Layer Skip, an end-to-end solution for accelerating LLMs from researchers at Meta FAIR. It achieves this by executing a subset of an LLM’s layers and utilizing subsequent layers for verification and correction. We’re now releasing inference code and fine-tuned checkpoints for this work. Model weights on Hugging Face ➡️ More details ➡️ We hope that releasing this work will open up new areas of experimentation and innovative new research in optimization and interpretability.

AI at Meta

156,638 次观看 • 1 年前

From training to inference at massive scale, delivering on the promise of AI depends on collaboration across open hardware and software. AMD and OpenAI are working together to tailor hardware like Instinct MI455X and Helios for where AI workloads are going, not just where they are today. Greg Brockman (Greg Brockman) on the power of our engineering partnership at #CES2026.

From training to inference at massive scale, delivering on the promise of AI depends on collaboration across open hardware and software. AMD and OpenAI are working together to tailor hardware like Instinct MI455X and Helios for where AI workloads are going, not just where they are today. Greg Brockman (Greg Brockman) on the power of our engineering partnership at #CES2026.

AMD

20,021 次观看 • 8 个月前