"Today's humanoid robots will not learn how to be dexterous despite the hundreds of millions, or perhaps many billions of dollars, being donated by VCs and major tech companies to pay for their training. The sensation of touch is one of the most complex systems in the human body, with the human hand containing 17,000 low-threshold mechanoreceptors for picking up light touches, which become denser toward the end of the fingertips."
"While AI has been trained on large amounts of speech-recognition and image-processing data, we do not have such a tradition for touch data. Brooks takes issue with the way both Musk's Tesla and AI-robotics company Figure are training their humanoid robots, with videos of humans performing tasks, assuming this will result in vastly improved dexterity."
"If the big tech companies and the VCs throwing their money at large-scale humanoid training spent only 20% as much but gave it all to university researchers I tend to think they would get closer to their goals more quickly."
Rodney Brooks, a veteran MIT roboticist and iRobot cofounder, argues that massive venture capital and tech company investments in humanoid robots represent misguided spending. He contends that humanoid robots cannot achieve the dexterity required for versatile assistants despite billions in funding. The human hand's complexity—containing 17,000 mechanoreceptors and intricate neural connections—remains extremely difficult to replicate. Brooks criticizes training methods using human video demonstrations, noting that touch data lacks the established training traditions of speech and image recognition. He suggests redirecting 20% of current humanoid robot funding to university researchers would accelerate progress toward actual dexterity goals more effectively than current large-scale corporate approaches.
#humanoid-robots #robot-dexterity #venture-capital-investment #touch-sensation-technology #ai-training-limitations
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