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The models are getting better everyday. This is a pretty contact-rich task, and forces us to reckon with the fact that our policies not only need to learn the quirks of different robots, but also have to do it in a way that generalizes to the fine-grained subtleties of... show more
61,885 просмотров • 2 месяцев назад •via X (Twitter)
Комментарии: 20

Thrilled to see it!

Impressive.

Amazing how naturally the robot performs. Curious to get your thoughts on how task level reasoning would eventually come in the GEN Models. Would a separate model eventually sit on top of GEN-1 for longer horizon tasks, the way Gemini Robotics paired ER 2 with a VLA?

impressive.

What really matters at this point is how much of it was actually achieved in one shot.

I think robotic arms will be the first large-scale robots that people use in their work and daily lives

Wow! Curious if this is the contribution mainly from the post-training team?

This is getting kinda crazy

Impressive!

I think friction is where robotics benchmarks meet reality. A policy that ignores material, pressure, wear, and contact variation may look intelligent in simulation but remain brittle on the factory floor.

The biggest breakthroughs in robotics will come from mastering the physics of the real world. Exciting progress 👏

the threaded nut is fascinating because the ending torque influences where it’ll end up

We operate a permitted commercial kitchen in SF serving real paying customers, and we're opening it up as a live training and evaluation site for robots (real orders as ground truth, egocentric capture from working cooks, food-safe protocols handled by us). Nobody's put a humanoid in front of a paying customer's order yet would love to show you what that could look like. Open to 15 min?

Oh - I see - they’re practicing for harvesting human organs. Tracks. AI’s can’t get embodied fast enough…

The wedging case is a good test because a visually plausible trajectory can still be wrong once friction changes. Recovery after that kind of failure would be really informative.

What gripper is this?

x algo doing it's work

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Actuator-level adaptation seems to be the hard part. Almost everyone ships one model per platform, which is why nobody in robotics has software margins. If GEN-1 moves across actuators without retuning, the moat stops being the robot. Precision is downstream of that.

通用人工智能领域的联合创始人,好优秀!真诚想认识一下,交个朋友✨
