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Turns out that doing In-context learning for robots is not that hard...

273,623 görüntüleme • 17 gün önce •via X (Twitter)

25 Yorum

ismaelvega profil fotoğrafı
ismaelvega17 gün önce

it's right behind me isn't it

Chenhao Li profil fotoğrafı
Chenhao Li17 gün önce

@chris_j_paxton I feel this is a not very well-defined area where we know how “OOD” the task is.

Chongkai Gao profil fotoğrafı
Chongkai Gao16 gün önce

What's the difference between in-context learning and those one-shot imitation learning papers from several years ago? I think there demo are very similar:

Kamal Gupta profil fotoğrafı
Kamal Gupta17 gün önce

I like the robot wearing meta glasses. Also wuji hands?

Isaac Sin profil fotoğrafı
Isaac Sin17 gün önce

nice @BillyYYan

Daneel profil fotoğrafı
Daneel17 gün önce

Oh my! Third in context learner robot in the last few weeks and first I’ve seen with a humanoid. Nice!

Samay Maini profil fotoğrafı
Samay Maini16 gün önce

@BillyYYan this is great!

seanpixel 🫧 profil fotoğrafı
seanpixel 🫧17 gün önce

@chris_j_paxton are those Aria glasses?

Anto Patrex profil fotoğrafı
Anto Patrex17 gün önce

Very true. But the real question is: how do we scale this data, and how accurate and reliable are these actions once they’re deployed in real production environments?

Ishmael59 profil fotoğrafı
Ishmael5917 gün önce

What happens if you move the bowl?

Aryan Dhawan profil fotoğrafı
Aryan Dhawan8 gün önce

How sensitive is it to the context you give it? Picking an example that actually disambiguates the task seems like it could become half the work.

Joseph Sottile 🌊 | Diffraction profil fotoğrafı
Joseph Sottile 🌊 | Diffraction17 gün önce

@chris_j_paxton Any reason for having your hands in that particular starting/neutral position?

Puzzle Paws profil fotoğrafı
Puzzle Paws17 gün önce

man, 'not that hard' on a clean table with two objects. real world generalization is the hard part. my cats would break this in ten seconds flat.

Armeen profil fotoğrafı
Armeen13 gün önce

In-context adaptation is the most promising route past per-task finetuning. The eval that would convince me: a demo given in one room, then executed in a room the policy never saw, with the object swapped for a same-category variant.

/ profil fotoğrafı
/16 gün önce

do a more complex grasp, like a hammer or something. Squishing a soft toy is trivial.

Roman Li | AI-powered GTM profil fotoğrafı
Roman Li | AI-powered GTM16 gün önce

Impressive. The product question is no longer whether a robot can learn in context, but whether a non-expert user can provide the right demonstration reliably. The teams that turn that teaching loop into a simple, observable UX will have a real adoption advantage.

Samuel Ekpe profil fotoğrafı
Samuel Ekpe17 gün önce

@xiaolonw This is cool

Oliver profil fotoğrafı
Oliver16 gün önce

And how does it look without the context?

nnnnn profil fotoğrafı
nnnnn16 gün önce

can it learn to wash the dishes this way?

Robert Blank profil fotoğrafı
Robert Blank16 gün önce

Just add some legs to increase the cost and complexity and you’ve got a humanoid

Andrew I. Christianson profil fotoğrafı
Andrew I. Christianson17 gün önce

VLA model?

Sadly life respecter profil fotoğrafı
Sadly life respecter17 gün önce

What robot is this. The arms look very human like

Krishna Nagam profil fotoğrafı
Krishna Nagam16 gün önce

Now I understand where robots get such robotic movements. Infact robot movements are more human like than the person teaching it.

Weijie Wang profil fotoğrafı
Weijie Wang15 gün önce

what is the Glasses, it is the secrete , how this demo work

ovoDRIZZYxo profil fotoğrafı
ovoDRIZZYxo16 gün önce

u need another bot, thats taking it out

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