OpenAI, a nonprofit created by Elon Musk and other tech entrepreneurs to make fundamental breakthroughs in artificial intelligence, has said that one of its big goals will be teaching robots to do the laundry and other household chores. OpenAI doesn’t want to make robot hardware itself but, rather, to supply the brains for off-the-shelf bots.
You might think that learning to fold underpants is a modest goal, but such dexterity and adaptability is one of the grand challenges of robotics. It also fits with the organization’s stated objective to “advance digital intelligence in the way that is most likely to benefit humanity as a whole.” Applying the sort of machine-learning techniques OpenAI is working on to robotics should, in fact, have huge practical benefits, and it will be a necessary component of any more general form of artificial intelligence.
OpenAI’s announcement is unsurprising given that it recently hired Pieter Abbeel, an academic who has pioneered the application of machine learning to robots. Abbeel and his students at the University of California, Berkeley, have been doing impressive work enabling robots to learn to perform complex tasks through trial and error, either in simulation or through real-world actions.
Rewarding certain behavior—an approach known as reinforcement learning—will probably become very common for industrial robots in the next few years. What’s cool is that you can accelerate this learning process simply by having many robots working on a task in parallel, sharing information as they go. And while OpenAI has committed to releasing its research, the various companies owned by Musk and other backers of OpenAI could certainly benefit from advances in these areas.
(Read more: OpenAI, “This Factory Robot Learns a New Job Overnight,” “Good Robot: Elon Musk’s Nonprofit Shows Where AI Is Going,” “Robot Toddler Learns to Stand by 'Imagining' It,” “Robots That Teach Each Other”)
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