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

273,623 Aufrufe • vor 17 Tagen •via X (Twitter)

25 Kommentare

Profilbild von ismaelvega
ismaelvegavor 17 Tagen

it's right behind me isn't it

Profilbild von Chenhao Li
Chenhao Livor 17 Tagen

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

Profilbild von Chongkai Gao
Chongkai Gaovor 16 Tagen

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:

Profilbild von Kamal Gupta
Kamal Guptavor 17 Tagen

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

Profilbild von Isaac Sin
Isaac Sinvor 17 Tagen

nice @BillyYYan

Profilbild von Daneel
Daneelvor 17 Tagen

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

Profilbild von Samay Maini
Samay Mainivor 16 Tagen

@BillyYYan this is great!

Profilbild von seanpixel 🫧
seanpixel 🫧vor 17 Tagen

@chris_j_paxton are those Aria glasses?

Profilbild von Anto Patrex
Anto Patrexvor 17 Tagen

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?

Profilbild von Ishmael59
Ishmael59vor 17 Tagen

What happens if you move the bowl?

Profilbild von Aryan Dhawan
Aryan Dhawanvor 8 Tagen

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.

Profilbild von Joseph Sottile 🌊 | Diffraction
Joseph Sottile 🌊 | Diffractionvor 17 Tagen

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

Profilbild von Puzzle Paws
Puzzle Pawsvor 17 Tagen

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.

Profilbild von Armeen
Armeenvor 13 Tagen

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.

Profilbild von /
/vor 16 Tagen

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

Profilbild von Roman Li | AI-powered GTM
Roman Li | AI-powered GTMvor 16 Tagen

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.

Profilbild von Samuel Ekpe
Samuel Ekpevor 16 Tagen

@xiaolonw This is cool

Profilbild von Oliver
Olivervor 16 Tagen

And how does it look without the context?

Profilbild von nnnnn
nnnnnvor 16 Tagen

can it learn to wash the dishes this way?

Profilbild von Robert Blank
Robert Blankvor 16 Tagen

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

Profilbild von Andrew I. Christianson
Andrew I. Christiansonvor 17 Tagen

VLA model?

Profilbild von Sadly life respecter
Sadly life respectervor 17 Tagen

What robot is this. The arms look very human like

Profilbild von Krishna Nagam
Krishna Nagamvor 16 Tagen

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

Profilbild von Weijie Wang
Weijie Wangvor 15 Tagen

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

Profilbild von ovoDRIZZYxo
ovoDRIZZYxovor 16 Tagen

u need another bot, thats taking it out

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