22nd January 2021 3:00 am 21st January 2021 12:30 pm Computer scientists from University of Texas at Arlington, USA, are exploring the use of AI and supercomputers for generating synthetic objects to train robots. Examples of 3D point clouds synthesised by the progressive conditional generative adversarial network (PCGAN) for an assortment of object classes. Credit: William Beksi William Beksi, assistant professor in UT Arlington’s Department of Computer Science and Engineering and founder of the university’s Robotic Vision Laboratory, is leading the research with a group including six PhD Computer Science students. Having previously interned at consumer robot producer iRobot, where researchers were interested in using machine and deep learning to train robots, Beksi said he was particularly interested in developing algorithms that enable machines to learn from their interactions with the physical world and autonomously acquire skills necessary to execute high-level tasks.