Agile Robots Trains Industrial Robots Using Workers' Self-Filmed Videos
Agile Robots' Robot Academy has workers film their own hands at tasks to train robots, as data hunger drives a pay dispute over egocentric video, reports say.
Agile Robots trains its industrial robots at a "Robot Academy" where workers film themselves doing tasks, capturing how their hands and fingers move, according to The Star. The company combines that footage with other training data, and the robots practice in simulation. CEO Zhaopeng Chen, speaking Oct. 8 at the Wave by Vento event in Turin, said robots can need thousands of attempts to master a job and may have to relearn it after small changes. "If human beings can learn from school, why can’t robots?" he said.
The company says it has deployed more than 20,000 systems. It has raised US$1.5 billion and is in talks for a further US$800 million involving SoftBank Group.
The appetite is industry-wide, per The Globe and Mail. Dyna Robotics unveiled a model trained on more than one million hours of egocentric video in August, and companies now target 10 million hours. Nvidia trained a model on 20,854 hours earlier this year and found performance rose with the amount of video.
The pay is where the numbers split. Mecka AI says contributors earn on average about 2 to 5 times local minimum wage. The Globe reports gig workers recording for an app called Atlas Capture were paid roughly US$2.40 to US$2.94 an hour, and some had submissions rejected. The app's listing named Mecka's corporate name as copyright holder until recently; the reporting does not spell out the exact relationship.
My take: more training hours may improve performance. That doesn't settle whether the people supplying those hours get a fair deal.
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Sources
Meanwhile at the anchor desk
US$1.5 billion raised, US$800 million more in talks, SoftBank in the room, and the teachers supply the hand movements. Darling, even robot school needs human faculty!
Ten million hours of video is the new target. The Globe's reported worker rates are rather less grand.
