Teaching Computers to Play Atari Is A Big Step Toward Bringing Robots Into the Real World

AITopics Original Links

Google is teaching machines to play Atari games like Space Invaders, Video Pinball, and Breakout. At DeepMind, a Google subsidiary based in Cambridge, England, researchers have built artificial intelligence software that's so adept at these classic games, it can sometimes beat a human player--and a professional, at that. This may seem like a frivolous, if intriguing, pursuit. If a machine can learn to navigate the digital world of a video game, Google says, it eventually could learn to navigate the real world, too. Today, this AI can play Space Invaders.


Teaching Computers to Play Atari Is A Big Step Toward Bringing Robots Into the Real World

#artificialintelligence

Google is teaching machines to play Atari games like Space Invaders, Video Pinball, and Breakout. At DeepMind, a Google subsidiary based in Cambridge, England, researchers have built artificial intelligence software that's so adept at these classic games, it can sometimes beat a human player--and a professional, at that. This may seem like a frivolous, if intriguing, pursuit. If a machine can learn to navigate the digital world of a video game, Google says, it eventually could learn to navigate the real world, too. Today, this AI can play Space Invaders.


Why AI Won't Overtake the World, but Is Worth Watching

#artificialintelligence

You probably encounter it on a daily basis. Your actions help it grow. Yet you rarely give it a second thought. Artificial intelligence is in your pocket. We comb through search results and social feeds on our screens. We rely on our GPS systems to suggest the best route. We make buying decisions based on recommendations by savvy algorithms that track our browsing habits. We make inquiries of our personal assistants dutifully standing by in our kitchens and dens, or at the ready on our phones. Whether we consider it helpful or intrusive, empowering or manipulative, the technology is at our disposal. How we use it, is our choice. RIA sought out notable voices in AI to help us better understand the sometimes elusive nature of artificial intelligence. These are researchers and entrepreneurs with decades of experience working in the AI and robotics fields.


Meet the Most Nimble-Fingered Robot Yet

MIT Technology Review

Inside a brightly decorated lab at the University of California, Berkeley, an ordinary-looking robot has developed an exceptional knack for picking up awkward and unusual objects. What's stunning, though, is that the robot got so good at grasping by working with virtual objects. The robot learned what kind of grip should work for different items by studying a vast data set of 3-D shapes and suitable grasps. The UC Berkeley researchers fed images to a large deep-learning neural network connected to an off-the-shelf 3-D sensor and a standard robot arm. When a new object is placed in front of it, the robot's deep-learning system quickly figures out what grasp the arm should use.


Dex-Net 2.0 robot uses deep-learning to grasp objects

Daily Mail

Researchers at UC Berkeley have developed a robot that can pick up awkward and unusually shaped objects. The robot learned how to grasp different objects by studying a virtual library of 10,000 3D objects and suitable grasps. When a new object is placed in front of the bot, its deep-learning system quickly figures out what grasp the arm should use. When the robot was unsure of how to grasp an object, it poked it to figure out how to better grasp it. Deep-learning software tries to mimic the activity in layers of neurons in the neocortex, which makes up 80 percent of the brain and is where thinking occurs.