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Gpt-6 astra can do in-context learning on mobile manipulation! • Different environment • Different camera angle • Different layout No text prompt, it infers from video It even chooses when to use end-effector or joint space Trace recording after ⬇️

Axel

4,570 subscribers

67,278 görüntüleme • 15 gün önce •via X (Twitter)

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Axel profil fotoğrafı

Axel15 gün önce

The agent is asked to establish a plan based on the demonstration only It self-corrects and retries if needed Honestly it's pretty mesmerizing to see, and it will keep getting faster

Axel profil fotoğrafı

Axel15 gün önce

The code is available here: We haven't completely cleaned it yet but your favorite agent will be able to understand our approach

Dhruv Diddi profil fotoğrafı

Dhruv Diddi15 gün önce

Nicely done! 💯🦾👏

David Dobáš profil fotoğrafı

David Dobáš15 gün önce

Look at the beautiful phone teleop interface

Axel profil fotoğrafı

Axel15 gün önce

woah who built that

Robert Scoble profil fotoğrafı

Robert Scoble15 gün önce

It is getting faster! Congrats.

Axel profil fotoğrafı

Axel15 gün önce

🫡

Andrew Lyubovsky profil fotoğrafı

Andrew Lyubovsky15 gün önce

Pretty Cool !!

Miguel Gregori profil fotoğrafı

Miguel Gregori14 gün önce

Cuando el entorno cambia y el robot no pide un manual nuevo, ahí hay diseño.

NAMAN RAJ profil fotoğrafı

NAMAN RAJ15 gün önce

Mind blown! 🤯 That's some advanced AI magic right there! 🧙‍♂️ What do you guys think, is this the future of human-AI collaboration?

AIwithMinal profil fotoğrafı

AIwithMinal15 gün önce

Pure artistic brilliance.

SEAR profil fotoğrafı

SEAR15 gün önce

this is exactly the kind of learning Sear is built around

ethereagle · building profil fotoğrafı

ethereagle · building15 gün önce

no text, video only. are those frames dumped straight into Astra's context, or is there a separate encoder in front? that's copy-with-the-API vs needing your stack.

Axel profil fotoğrafı

Axel15 gün önce

dumped straight in

atharva ☆ profil fotoğrafı

atharva ☆15 gün önce

woah incredible

Axel profil fotoğrafı

Axel15 gün önce

yeah am pretty stoked

Aaron profil fotoğrafı

Aaron15 gün önce

so cool! 😎

Axel profil fotoğrafı

Axel15 gün önce

couldn't believe it at first tbh

Tepulous profil fotoğrafı

Tepulous15 gün önce

$20/min .....

Axel profil fotoğrafı

Axel15 gün önce

not if you use kv-caching

RealMan Robotics profil fotoğrafı

RealMan Robotics15 gün önce

The shift from simulation to real-world manipulation is the part that really matters. Curious to see how far this generalization can scale across tasks and environments.

AI Quanting profil fotoğrafı

AI Quanting14 gün önce

The control space choice is the bit Id want to see stressed. Does it switch to joint space when the demo path is actually constrained, or does it settle per task type regardless?

Hibrinix profil fotoğrafı

Hibrinix15 gün önce

Meanwhile your future mobile phone

Amogh Shrivastava profil fotoğrafı

Amogh Shrivastava15 gün önce

that looks peak

Axel profil fotoğrafı

Axel15 gün önce

That's because it is

Degenpark profil fotoğrafı

Degenpark15 gün önce

end-effector choice is huge

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okay another demo fo Gemma4 + Falcon Perception for automated video segmentation & tracking, no human prompts needed the idea: you feed Gemma4 a few sampled frames and ask it to describe what it sees. those descriptions get passed to Falcon Perception which segments and tracks them across the full video (using ByteTrack you can steer what Gemma4 focuses on with different prompt levels: describe by visible text or brand -> dog with number 2 bib describe by spatial position -> horse on the right, horse in center, horse on the left describe by relationships -> rhinoceros walking with zebra same pipeline, different instructions ->different segmentation results. zero human labeling from raw video to tracked output. all local on M3 using mlx-vlm Prince Canuma Maziyar PANAHI Work done by Sanath Narayan Check our Falcon Perception repo:

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