๐๐ก๐๐ญ ๐ฆ๐๐ค๐๐ฌ ๐ญ๐๐ฅ๐๐จ๐ฉ๐๐ซ๐๐ญ๐ข๐จ๐ง ๐๐๐ญ๐ ๐๐๐ญ๐ฎ๐๐ฅ๐ฅ๐ฒ ๐ฎ๐ฌ๐๐๐ฎ๐ฅ? ๐ฆพ
๐ผ๐๐๐ ๐๐๐๐๐ โ ๐๐๐๐๐๐ ๐๐๐๐.
For Physical AI, the value of a teleoperation session comes down to what the model can actually learn from it.
Clean movements, correct task execution, clear camera views, synchronized data, useful state information, and consistent human validation all matter.
A good demonstration isnโt just a completed task. Itโs a clean action-observation pair that teaches the model something reliable about the physical world.
โโโโโโโโโโ
=> ๐๐ฉ๐ข๐ตโ๐ด ๐ธ๐ฉ๐บ ๐ฅ๐ข๐ต๐ข ๐ฒ๐ถ๐ข๐ญ๐ช๐ต๐บ ๐ฎ๐ข๐ต๐ต๐ฆ๐ณ๐ด ๐ฎ๐ฐ๐ณ๐ฆ ๐ต๐ฉ๐ข๐ฏ ๐ด๐ช๐ฎ๐ฑ๐ญ๐บ ๐ค๐ฐ๐ญ๐ญ๐ฆ๐ค๐ต๐ช๐ฏ๐จ ๐ฎ๐ฐ๐ณ๐ฆ ๐ฉ๐ฐ๐ถ๐ณ๐ด!
At PrismaX, the focus is on building data that can actually contribute to better Vision-Language-Action models and, ultimately, more capable robots.
โโโโโโโโโโ
๐ฐ๐ ๐๐๐โ๐๐ ๐๐๐๐๐๐๐๐๐๐ ๐๐ ๐๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐๐ ๐ ๐๐๐, ๐๐๐๐๐ ๐ ๐๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐ ๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐ ๐๐.
๐๐๐๐๐๐๐ข ๐๐๐๐๐. ๐ ๐๐๐๐๐ ๐๐๐๐๐๐.
gPrisma!
๐๐๐๐ข๐๐๐ฅ ๐๐จ๐ฎ๐ซ๐๐๐ฌ ๐จ๐ ๐๐ซ๐ข๐ฌ๐ฆ๐๐ https://t.co/RSQZFK5P23
CC: @vivianrobotics | @MaxC16134@realAltcoiner
6/6
Maybe the goal shouldn't be teaching robots a perfect world.
It should be teaching them how to handle an imperfect one.
Because when the unexpected happens, that's when intelligence really gets tested.
Real experience โ Better learning โ More capable robots.
@PrismaXai
1/6
๐๐จ๐๐จ๐ญ๐ฌ ๐๐จ๐ง'๐ญ ๐ฅ๐๐๐ซ๐ง ๐๐ซ๐จ๐ฆ ๐ฉ๐๐ซ๐๐๐๐ญ ๐ฐ๐จ๐ซ๐ฅ๐๐ฌ.
A real robot will eventually face something unexpected.
An object moves.
The grip isn't perfect.
The lighting changes.
What happens next matters.
5/6
With PrismaX, human operators create real-world robot experiences, while validators help evaluate the quality of those demonstrations.
The goal isn't simply to collect everything.
It's to identify experiences that can actually contribute to better Physical AI.
just got my WL ticket: PF-87E3-8QX1-71WW-N5PJ ๐
they are dropping nft collection on Robinhood
follow them, might be the next alpha https://t.co/f63lAJMg8D