As a social media platform with global reach, Facebook leans extensively on its artificial intelligence and machine-learning systems to keep the site online and harmful content off it (at least, some of the time). Following its announcement at the start of the month regarding self-supervised learning, computer vision, and natural language processing, Facebook on Monday shared details about three additional areas of research that could eventually lead to more capable and curious AI.
"Much of our work in robotics is focused on self-supervised learning, in which systems learn directly from raw data so they can adapt to new tasks and new circumstances," a team of researchers from FAIR (Facebook AI Research) wrote in a blog post. "In robotics, we're advancing techniques such as model-based reinforcement learning (RL) to enable robots to teach themselves through trial and error using direct input from sensors."
Specifically, the team has been trying to get a six-legged robot to teach itself to walk without any outside assistance. The hexapod begins its existence as a pile of legs with no understanding of its surroundings. Using a reinforcement-learning algorithm, the robot slowly figures out a controller that will help it meet its goal of forward locomotion. And since the algorithm utilizes a recursive self-improvement function, the robot can monitor the information it gathers and further optimize its behavior over time. That is, the more experience the robot gains, the better it performs.
Read the full story, "Facebook Research is developing touchy-feely curious robots," at www.engadget.com.
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