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

273,623 views • 17 days ago •via X (Twitter)

25 Comments

ismaelvega's profile picture
ismaelvega17 days ago

it's right behind me isn't it

Chenhao Li's profile picture
Chenhao Li17 days ago

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

Chongkai Gao's profile picture
Chongkai Gao16 days ago

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's profile picture
Kamal Gupta17 days ago

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

Isaac Sin's profile picture
Isaac Sin17 days ago

nice @BillyYYan

Daneel's profile picture
Daneel17 days ago

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

Samay Maini's profile picture
Samay Maini16 days ago

@BillyYYan this is great!

seanpixel 🫧's profile picture
seanpixel 🫧17 days ago

@chris_j_paxton are those Aria glasses?

Anto Patrex's profile picture
Anto Patrex17 days ago

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's profile picture
Ishmael5917 days ago

What happens if you move the bowl?

Aryan Dhawan's profile picture
Aryan Dhawan8 days ago

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's profile picture
Joseph Sottile 🌊 | Diffraction17 days ago

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

Puzzle Paws's profile picture
Puzzle Paws17 days ago

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's profile picture
Armeen13 days ago

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.

/'s profile picture
/16 days ago

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

Roman Li | AI-powered GTM's profile picture
Roman Li | AI-powered GTM16 days ago

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's profile picture
Samuel Ekpe16 days ago

@xiaolonw This is cool

Oliver's profile picture
Oliver16 days ago

And how does it look without the context?

nnnnn's profile picture
nnnnn16 days ago

can it learn to wash the dishes this way?

Robert Blank's profile picture
Robert Blank16 days ago

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

Andrew I. Christianson's profile picture
Andrew I. Christianson17 days ago

VLA model?

Sadly life respecter's profile picture
Sadly life respecter16 days ago

What robot is this. The arms look very human like

Krishna Nagam's profile picture
Krishna Nagam16 days ago

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

Weijie Wang's profile picture
Weijie Wang15 days ago

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

ovoDRIZZYxo's profile picture
ovoDRIZZYxo16 days ago

u need another bot, thats taking it out

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