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1X World Model Scaling Evaluation for Robots

1X

130,162 subscribers

385,680 次观看 • 1 年前 •via X (Twitter)

Anya Rossi• Live Now

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10 条评论

1X 的头像

1X1 年前

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dar 的头像

dar1 年前

THE MATRIX IS REAL! EVALUATING ROBOT MODELS WORKS!!! BIRDS ARE NOT FAKE?? SCALING LAWS ARE PROVEN!!!!!😩

TestingCatalog News 🗞 的头像

TestingCatalog News 🗞1 年前

Brilliant 🤖🤖🤖

frishtik de AI weirdo 的头像

frishtik de AI weirdo1 年前

do yall live in the woods what’s up

1X 的头像

1X1 年前

The artsy fartsy guys keep taking the engineers into the woods... Working on resolving this internally

Daniel Ho 的头像

Daniel Ho1 年前

📺

Humanoids daily 的头像

Humanoids daily1 年前

An interesting insight from the video: the finding that the most valuable data for scaling the world model comes from NEO autonomously interacting with real environments—"succeeding and failing in interesting and diverse ways". The robot itself is the data engine.

DeBarra Shaw 的头像

DeBarra Shaw1 年前

Impressive design and visionary approach. Can’t wait to see more!

Ted Xiao 的头像

Ted Xiao1 年前

Scalable and predictive evaluation is one of the biggest bottlenecks in robotics, congrats @itsdanielho and the whole 1X team!

✧Heavens✧ 的头像

✧Heavens✧1 年前

Beautiful! This is a game-changer, bridging reality and simulation to rapidly accelerate the evaluation of generalist robots, it's one of the most important aspects of the process. Seems like NEO will be one of the first commercially available robots for house use, looking forward to it, the future is bright. 👀✨

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Every home is different. That means that to build a useful home robot, we must be able to perform zero-shot generalization on a wide range of tasks. Humanoid company 1X has a solution: world models. 1X Director of Evaluations Daniel Ho joins us on RoboPapers to talk about: - why world models are the future for scaling robot learning - how to use world models for robot control - what world models unlock for evaluating robot model performance - how we can hill-climb from here to general purpose robots Watch Episode #61 of RoboPapers, with Michael Cho - Rbt/Acc and Chris Paxton, now!

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