Stanford researchers’ DERL (Deep Evolutionary Reinforcement Learning) is a novel computational framework that enables AI agents to evolve morphologies and learn challenging locomotion and manipulation tasks in complex environments using only low level egocentric sensory information.
A team of researchers from Institut de Robòtica i Informàtica Industrial and Harvard University recently introduced 3DPeople, a large-scale comprehensive dataset with specific geometric shapes of clothes that is suitable for many computer vision tasks involving clothed humans.
To enable both content creators and end users to seriously restyle their apps’ interfaces while maintaining content detail clarity essential to their usability, researchers from Stanford have proposed ImagineNet, a novel and powerful new tool for interface customisation.
Last October Stanford University announced plans to create an institute built for artificial intelligence research and development. Today, the school made good on its pledge, launching the Stanford Institute for Human-Centered Artificial Intelligence (Stanford HAI) with a mission “to advance AI research, education, policy, and practice to improve the human condition.”
Earlier this week the Association for Computational Linguistics (ACL) 2018 announced its Best Two Short Papers, neither of which had yet been published. Today the AI community got its first look at one of the winners when Know What You Don’t Know: Unanswerable Questions for SQuAD was released on arXiv.