WE are hiring @worldengine_ai. We have three open roles:
1. Strategic Project Lead, Robotics Ops
2. Research/Software Engineer, Robotics Data (esp. real-to-sim)
3. Research PM, Robotics GTM
Internship is also available. Apply here: https://t.co/S5KXNDjTSc
It has never been so exciting to push the boundary of physical AGI. We stay quiet and move fast. Months of work, extremely focused. Incredibly proud of the team at @worldengine_ai !
We are building the infrastructure for future robots.
More exciting to come, stay tuned :)
Introducing OM-1, our first robot foundation model, zero-shot generalizing to any robot: table-top arms, industrial arms and humanoids.
- learned directly from human manipulation data
- no teleop/robot data
- close to human-level dexterity and efficiency
- multi-robot collab
iβve downloaded xiaohongshu to look at robot videos.
x dot com has the occasional demo reel, whereas my entire feed on xsh are real robots recorded by everyday people for extended periods
The Trump administration plans to announce bans on imports of Chinese robots and power inverters later today. It is being reported here on X that a Chinese AI model ban will also be announced today, but that is not in the Reuters article.
This is interesting, with different end effector action spaces it learns to generalize. Wondering how good the performance is and how much data is used for that specific hand
Why create robot intelligence for just one hand, when we could have it learn from many?
GEN-1, our latest embodied foundation model, now supports a broad range of end effectors from 5-finger hands, to specialized tools, and everything in between.
Brutally hard, especially when it comes to dex hand. We (https://t.co/qQXz00Gbfp) started robotics data from day0, no pivot. We believe physical AGI is all about data.
The full stack team, laser focusing on dexterity and diversity for roboticsπͺ
The inbound from new robotics data vendors has been nonstop since last November. Half the companies that messaged us back then have since pivoted to something else. Collecting high quality robotics data is just brutally hard, and the market keeps proving it
The data ops team @sundayrobotics is genuinely world-class, led by the one and only @perryzjia. Come join us, weβre hiring :)
Are you training a VLA or WAM? I've been asked this question 100x by candidates and investors. My answer is simple - the model will win with:
- densified supervision
- trillions of diverse action tokens
- inference efficient model with right capacity.
Buzz words does not matter
Humanoid robots don't need to look human.
Meet Eno, our first general-purpose robot.
Not a machine pretending to be human, but intelligence given a body.
At Genesis, weβre building a future where robots donβt feel cold or distant, but capable, calm, and ready to help.
Available Q4 this year.
As always, robotics is more systemic than a foundation model. From motors, control, embedded system, data operations, models, all the way down to deployment.
That's the beauty of robotics - full stack!
I want to offer some unsolicited advice to computer vision researchers jumping into robotics. Don't focus too much on VLMs, VLAs etc. That's fine, but the real action is at the sensorimotor level. Most of the open problems in robotics are in manipulation, which is about hand-object interaction, and contacts and forces are central. Proprioception and tactile sensing are as important as vision. Don't get seduced by cherry-picked demos. You can't do robotics without doing robotics.
Using WUJI hand 1 for long time, the dexterity it can achieve is very impressive. Hand2 is a step further when I saw it for the first time. A lot of features I like - less over-heating, backdrivable, and resolved backlash (most important).
Looking forward to the mass production!
#RSS2026 Call for participants π’
Excited to announce our RSS 2026 Workshop: Post-Training for Robotics Foundation Models, together with the first Real-World Reinforcement Learning Challenge!
The workshop is held on July 13 in Sydney.
https://t.co/c3Dy1CrI0Lγ
Huge congrats to @gs_ai_ on GENE-26.5.
Human level dexterity is finally here. Working alongside the Genesis team has been one of the most rewarding journeys---late nights, hard problems, and a shared belief that robotics is far from solved.
Proud that WorldEngine contributed to the "fuel for the engine." Dexterity got pushed to the limit across hardware, data, models, and system integration---and we're down to solve it one data point at a time.
βοΈ [email protected]