Medical workers are our heroes as the COVID-19 outbreak continues with deaths and confirmed cases rising. A CNN survey found that healthcare systems are coming under strain because of the increasing number of patients infected by the coronavirus. Partners Healthcare is supporting patients in the COVID-19 outbreak by using AI to detect those infected and those showing signs of the virus. Healthcare workers at Partners Healthcare understand the current crisis because of high patient numbers experienced and are working round the clock. One question that comes to mind as COVID-19 pandemic continues is: How responsible is the current use of AI to combat the outbreak?

This article is made possible by Intel's GameDev BOOST program -- dedicated to helping indie game developers everywhere achieve their dreams Throughout Kevin He's career in the tech and gaming industries, something has always bothered him. While rendering and other technologies evolved tremendously over time, animation woefully lagged behind. As an engineer, He wanted to find an efficient way to create more lifelike animations, and he was convinced that advanced physics simulation and AI could solve that problem. So in 2014, He struck out on his own to start DeepMotion. The goal of the San Mateo, California-based company is to provide developers with powerful software development kits (SDK) that'll allow them to create realistic animations for games and other applications.

Artificially intelligent software has now picked up a devastating new skill after observing humans. A pair of brainiacs – Jessica Hodgins at Carnegie Mellon University in the US and Libin Liu at DeepMotion, a Silicon Valley startup creating realistic graphics using AI – have trained a virtual character that can show off its believable b-ball skills in real time. It's harder than it sounds, honest. The joints in the arms, hands, and fingers have to be realistically simulated in order to demonstrate its basketball powers. And even though it exists in a virtual world, the character has to take gravity into account, and maintain its balance and control while moving.

Abstract-- We present a novel human-aware navigation approach, where the robot learns to mimic humans to navigate safely in crowds. The presented model referred to as DeepMoTIon, is trained with pedestrian surveillance data to predict human velocity.The robot processes LiDAR scans via the trained network to navigate to the target location. We conduct extensive experiments to assess the different components of our network and prove the necessity of each to imitate humans. Our experiments show that DeepMoTIon outperforms state-ofthe art in terms of human imitation and reaches the target on 100% of the test cases without breaching humans' safe distance. I. INTRODUCTION Robots are gradually moving from factories and labs to streets, homes, offices, and healthcare facilities.

Leading artificial intelligence driven, physics-based animation to new heights.