Coline Devin

65 posts

Coline Devin

Coline Devin

@ColinearDevin

GeneralistAI Prev: Google Deepmind Robotics

Tham gia Ocak 2021
174 Đang theo dõi686 Người theo dõi
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Generalist
Generalist@GeneralistAI·
GEN-1 puts plushies into polybags, in a warehouse outside the lab in New Hampshire.
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Andy Zeng
Andy Zeng@andyzengineer·
I love this one, because deploying a robot then “integrating with customer APIs” is not fun. But a lot simpler when your robot can push the same buttons as a human 👆or use a touch screen. Also, GEN-1 has memory too — it learns to “remember” which sock it put away, then taps.
Generalist@GeneralistAI

GEN-1 sorts socks and uses a touchscreen stylus. Done in collaboration with a partner on the Generalist platform. More on this soon.

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Generalist
Generalist@GeneralistAI·
GEN-1 puts pens into zipper bag. Robot’s view, pixels into the model.
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Felix Wang
Felix Wang@felixwyw·
As a PhD student, I worked on methods to generalize across motion, objects, lighting, backgrounds, etc. Each is hard, and there’s always a long tail. (E.g. my robot still can’t handle new camera views—hence the “Don’t move! Thx :)” sign.) But if you have enough data to train from scratch, many of these generalization problems start to disappear. You get them almost “for free.” What’s powerful is the clarity you get when you start from the goal, not from a favored method: data is a key bottleneck to remove on the path to physical AGI. And working backwards from first principles, there may be ways to solve the data problem that aren’t actually that expensive. That unlocks the freedom to train from scratch with simple methods, not crutches.
Felix Wang tweet media
Pete Florence@peteflorence

goals are more powerful than methods

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Generalist
Generalist@GeneralistAI·
This is GEN-1 putting paper bills into a wallet. Paper has always been deceptively hard for robots. Thin, deformable, and unforgiving—it bends, folds, and slips. Not precise, you miss. Too much force, you crumple. Easy for humans. But for robots, it’s a full-stack challenge.
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Generalist
Generalist@GeneralistAI·
Hear more about GEN-1 and improvisational intelligence from our own researchers @coolboi95 and @felixwyw
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Coline Devin
Coline Devin@ColinearDevin·
It's phase change in mastery when you move from measuring success rates as a percentage to counting successes in a row.
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Generalist
Generalist@GeneralistAI·
We ran a live demo @nvidia GTC last week, but the real story is how quickly we got it running. The system was up and running in days, not weeks. This is a step toward robots that can be deployed quickly without task-by-task programming. How we made it happen👇 🧵 (1/6)
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Pete Florence
Pete Florence@peteflorence·
At the booth live at #NVIDIAGTC! The hockey sticks are out, and the models are rolling. At Generalist we’re excited to be here as Preferred Model Partner with @Universal_Robot, the world’s #1 cobot manufacturer by volume!
Generalist@GeneralistAI

Happening now at #NVIDIAGTC: Generalist’s GEN-0 model autonomously packing phones on @Universal_Robot arms in our first public demo. To move robotics beyond the lab, systems need to operate in real time on industrial hardware. See the demo below, and stop by booth #1840 👇🤖

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Anirudha Majumdar
Anirudha Majumdar@Majumdar_Ani·
Generalist robots need a generalist evaluator. But how do you test safety without breaking things? 💥 🌎 Introducing our new work from @GoogleDeepMind: Evaluating Gemini Robotics Policies in a Veo World Simulator veo-robotics.github.io 🧵👇
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