DeepMind robotics lead says general-purpose robots remain far from practical use
A frontline researcher says robot models still lack the generalization and reliability for real use, so aggressive humanoid timelines deserve a discount.
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Keerthana Gopalakrishnan, research lead for Gemini Robotics at Google DeepMind, says robotics models remain in something like their GPT-2 era, still far from broad practical use.
She made the assessment on the October 3 episode of The Cognitive Revolution, as relayed by the show's notes. She argued that despite recent demos of robots learning tasks from a few or even one human demonstration, the range of teachable tasks and cross-embodiment generalization still fall short of the versatility and reliability real-world use demands.
On this summer's viral Robot Olympics in China, where humanoids ran faster than the fastest humans, she said running on a flat track is relatively easy to train in simulation and footspeed is not the limiting factor for robot utility; her team focuses on practical value instead.
This is her personal view on the show; the episode notes carry no transcript, and DeepMind has not issued an official position.