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Introducing WALL-WM, our open-source World Model for embodied AI and the next piece of our open-source robotics stack. Carving World Action Modeling at the Event Joints Read the blog: Why it matters WALL-WM shifts robot world modeling from fixed-length action chunks to event-grounded video-action pretraining. It learns around events...

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X Square Robot

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42,346 次观看 • 5 个月前 •via X (Twitter)

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Junfan Zhu 朱俊帆 ✈️ IROS 的头像
Junfan Zhu 朱俊帆 ✈️ IROS5 个月前

Excited to have @XSquareRobot presenting a lightning talk on WALL-WM at @saturdayrobotic Research Night during @CVPR 2026 on June 6. Looking forward! 👉🏻

Ruili Feng 的头像
Ruili Feng5 个月前

A great work from the Team! Stay tuned!

RoboHub🤖 的头像
RoboHub🤖5 个月前

Huge congrats, two major open-source releases back to back is a serious statement for embodied AI 🎉🎉🎉

X Square Robot 的头像
X Square Robot5 个月前

Thank you! Really appreciate it. We see open source as the fastest way to move embodied AI forward, and this week is just the beginning. More to share soon.

Skaltek 的头像
Skaltek5 个月前

The useful signal is not just “robot world model,” it is the packaging: open weights/code plus explicit event/action boundaries. Embodied AI needs reproducible eval surfaces before teams can tell progress from demo polish.

AIKeaton UK 的头像
AIKeaton UK5 个月前

This is the interesting bit for me. Modelling around contact, grasp, lift etc feels much closer to how real manipulation actually breaks down.

Nurvai - The Data Layer for Physical AI 的头像
Nurvai - The Data Layer for Physical AI5 个月前

Interesting shift away from fixed action chunks toward event centered modeling. Feels more aligned with how manipulation actually unfolds through contact, grasp, and transition points. Do you think event grounded representations generalize better to long horizon tasks?

gzrer 的头像
gzrer5 个月前

great job!

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21,317 次观看 • 4 个月前

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99,944 次观看 • 1 年前

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332,156 次观看 • 3 个月前

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Yutong Bai

180,726 次观看 • 1 年前

🤩Excited to share SANA-WM: a 2.6B open-source world model for minute-scale 720p video generation. Given one image + text + a 6-DoF camera trajectory, it synthesizes action-controllable 60s worlds on a single GPU. Project: Paper:
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🤩Excited to share SANA-WM: a 2.6B open-source world model for minute-scale 720p video generation. Given one image + text + a 6-DoF camera trajectory, it synthesizes action-controllable 60s worlds on a single GPU. Project: Paper:

Haoyi Zhu

124,794 次观看 • 6 个月前

Introducing Praxis-1, an open-weight World Action Model that turns our video pre-training expertise into real world control for robots. Robot demonstration data is limited. But video data is infinite. Praxis-1 extends our bet that the best policy models will learn from video, and use that scale to bring embodied intelligence to every industry. Praxis-1 is built on our large-scale video pre-training and real-time infrastructure, and acts as a policy model for robotics developers and researchers that works across any embodiment or environment, no matter how complex. We are actively testing with early partners including Noble Machines, Standard Bots and Ultra, and will be releasing the weights publicly in the coming months. Learn more and request early access at
1:54

Introducing Praxis-1, an open-weight World Action Model that turns our video pre-training expertise into real world control for robots. Robot demonstration data is limited. But video data is infinite. Praxis-1 extends our bet that the best policy models will learn from video, and use that scale to bring embodied intelligence to every industry. Praxis-1 is built on our large-scale video pre-training and real-time infrastructure, and acts as a policy model for robotics developers and researchers that works across any embodiment or environment, no matter how complex. We are actively testing with early partners including Noble Machines, Standard Bots and Ultra, and will be releasing the weights publicly in the coming months. Learn more and request early access at

Runway

120,141 次观看 • 1 个月前