Built an SO-101 pick and place simulation using GPT-6 Astra
Built an SO-101 pick-and-place simulation where Astra produces structured observations and Jev returns typed decisions with probability scores.
The original post
Built an SO-101 pick and place simulation using GPT-6 Astra and @typesafeai Jev.
Astra reads overhead and wrist camera images and produces structured observations and Jev returns typed decisions with probability scores.
A separate local controller carries out the movements and checks that the arm stays within its limits and is ready for each step. The models never directly control the motors.
A fixed pick and place sequence probably doesnt need this much decision making. I m using it as a testbed for situations where observations are uncertain and the system needs to decide whether to act wait or stop.
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under video, animation & media. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the video, animation & media page.
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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post