>
Why Geological Maps Are the Best Investment You've Never Heard Of
High School Student Discovers 1.5 Million Potential New Astronomical Objects...
UK Supreme Court says legal definition of 'woman' excludes trans women, in landmark ruling
Major Problem in Physics Could Be Fixed if The Whole Universe Was Spinning
Kawasaki CORLEO Walks Like a Robot, Rides Like a Bike!
World's Smallest Pacemaker is Made for Newborns, Activated by Light, and Requires No Surgery
Barrel-rotor flying car prototype begins flight testing
Coin-sized nuclear 3V battery with 50-year lifespan enters mass production
BREAKTHROUGH Testing Soon for Starship's Point-to-Point Flights: The Future of Transportation
Molten salt test loop to advance next-gen nuclear reactors
Quantum Teleportation Achieved Over Internet For The First Time
Watch the Jetson Personal Air Vehicle take flight, then order your own
Microneedles extract harmful cells, deliver drugs into chronic wounds
SpaceX Gigabay Will Help Increase Starship Production to Goal of 365 Ships Per Year
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. "Generally speaking, locomotion is a very difficult task in robotics and this is what it makes it very exciting from our perspective," Roberto Calandra, a FAIR researcher, told Engadget. "We have been able to design algorithms for AI and actually test them on a really challenging problem that we otherwise don't know how to solve."