Researchers Debate Why Robotics Trails AI Progress
Sara Hooker questions what unlocked fast AI gains that robotics cannot tap.
Sara Hooker posted that AI moved quickly due to specific accelerants unavailable to physical robots. Yue Wang replied that robotics is a system problem lacking societal infrastructure and stored knowledge. Other replies attributed the gap to skill shortages, noted hardware records advancing separately, compared the lag to past vision versus NLP divides, and observed that robotics may trail AI by several years. Yann LeCun added that the messy real world sustains the Moravec paradox. The visible replies on X present these contrasting attributions without a single consensus.
My husband asked me yesterday why is AI moving at lightspeed while robotics feels slower? I think its a really interesting question and speaks to what unlocked mainstream AI over the last decade—and why physical robots can't easily tap into those same accelerants.
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7 postsYW 
Yue Wang@yuewang314@sarahookr My take is robotics is a system problem and there is no societal infrastructure, as you mentioned, no knowledge stored.
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L( Leshem (Legend) Choshen 🤖🤗 @ACL @ICML@LChoshen@sarahookr Remember how vision asked that about nlp?
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KA kache@yacineMTB@sarahookr It is because a severe lack of skill
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SR Sebastian Raschka@rasbt@sarahookr Very interesting. I would say that robotics moves very fast, too but progress is mostly on the hardware side (e.g., the new sprint record couple of days ago). I guess it maybe also feels slower because fewer people work in it and use it, so we talk about it less?
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TM Tanishq Mathew Abraham, Ph.D.@iScienceLuvr@sarahookr Robotics isn't moving at lightspeed? It feels to me to be following a similar trajectory as AI but a few years behind basically. It's like we're in the GPT-3 era of robotics not the ChatGPT era. But I am an outsider here so I could very well be wrong!
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