[HN Gopher] Real-time action chunking with large models
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       Real-time action chunking with large models
        
       Author : pr337h4m
       Score  : 65 points
       Date   : 2025-06-17 19:39 UTC (1 days ago)
        
 (HTM) web link (www.pi.website)
 (TXT) w3m dump (www.pi.website)
        
       | jauntywundrkind wrote:
       | Anyone have good intro recommendations for VLAs?
        
         | lachyg wrote:
         | (I work at Pi.)
         | 
         | We open-sourced Pi0 (referenced in this post):
         | https://github.com/Physical-Intelligence/openpi
        
       | fennecbutt wrote:
       | Alright, I'm building the robot project I was putting off. This
       | is so fucking cool.
       | 
       | Excellent work!
        
       | UltraSane wrote:
       | I love the implications of a robot that can plug in Ethernet
       | cables.
        
         | meepmorp wrote:
         | "Soon, a robot will fix the cables in the server room for me!"
        
       | b0a04gl wrote:
       | rtc handling 300ms+ delay and still pulling off tasks like
       | plugging ethernet is kinda nuts. what i'm not getting is but
       | how's it keeping the control loop stable without retraining? some
       | sort of latent plan caching?
        
         | kvablack wrote:
         | It uses an inpainting algorithm (adapted from image generation
         | literature) to produce future actions that are consistent with
         | the current trajectory. It's sort of like warm-starting from a
         | cached plan, although the plan isn't latent, it's directly in
         | action space. Hopefully that answers your question -- there are
         | many more details in the blog post and paper :)
        
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