"Tesla CEO Elon Musk has bet his EV maker on selling millions of humanoid robots, prognosticating earlier this month that the initiative could eventually make up a whopping 80 percent of Tesla's value. He's promised that the company's Optimus robot could generate over $10 trillion in revenue in the long term, orders of magnitude more than the amount of money the carmaker made last year."
"While the current crop of robot companies are using machine learning to physically teach humanoid robots new tricks, "we do not have such a tradition for touch data," Brooks argued. "To think we can teach dexterity to a machine without understanding what components make up touch, without being able to measure touch sensations, and without being able to store and replay touch is probably dumb," he wrote."
Optimistic projections foresee humanoid robots becoming a dominant economic asset, with claims of trillions in potential revenue and major increases in market capitalization. Large investments target bipedal androids intended for household tasks and industrial uses. Critics emphasize that simulating human touch and achieving true dexterity remain unsolved problems despite many articulated robotic hands. Machine learning trains physical behaviors, but tactile data collection, measurement, storage, and replay traditions are lacking. Realizing mass-market humanoid robots therefore depends on breakthroughs in tactile sensing and dexterity that are not yet in hand.
Read at Futurism
Unable to calculate read time
Collection
[
|
...
]