Researchers have developed an AI-powered robot they claim can beat the physical marble game Labyrinth faster than humans are capable of. Thomas Bi and Raffaello D'Andrea of ETH Zurich created CyberRunner, which combines model-based reinforcement with the dexterity required to beat a game that requires physical skill, coordination and precision. For the uninitiated, the aim of the game is to guide a marble through a maze without falling into any holes. The player controls the movement of the ball by rotating two dials, which tilt the board. A camera observes the game and an algorithm learns more about it from each attempt.

Nvidia has demonstrated a robot with a groundbreaking AI which learns to complete tasks by observing the actions of a human. The researchers, led by Stan Birchfield and Jonathan Tremblay, claim their development is a'first of its kind' deep learning-based system. "For robots to perform useful tasks in real-world settings, it must be easy to communicate the task to the robot; this includes both the desired result and any hints as to the best means to achieve that result. With demonstrations, a user can communicate a task to the robot and provide clues as to how to best perform the task." Nvidia's robot is powered by the firm's TITAN X graphics cards which features 3584 NVIDIA CUDA cores running at 1.5GHz for a total performance of around 11 TFLOPS.

Every day, more than 1 million people in the United States require physical assistance to get dressed, whether because of injury, permanent disability, age, or other debilitating factors. To alleviate the problem, researchers from Georgia Tech built a deep learning-equipped robot that can help people get dressed. "What the robot is trying to do is to take the person's perspective of what a person is feeling during assistance," said Zachary Erickson, a robotics Ph.D. Student at Georgia Tech. "When the robot is doing this, it's using what it feels on its fingertips or its gripper and saying, what do I think a person is feeling while being dressed?" The robot, named PR2, was trained using NVIDIA Tesla V100 GPUs on the Amazon Web Services cloud with the cuDNN-accelerated Keras and TensorFlow deep learning frameworks.