AI with AI

Andy and Dave discuss a series of announcements: President Trump signs an Executive Order to prioritize and promote AI; the U.S. Department of Defense releases its 2019 AI Strategy; DARPA announces an Intelligent Neural Interface program focused on improving neurotechnology, and DARPA announces Guaranteeing AI Robustness against Deception (GARD), intended as an almost immune-system like approach to increase the resistance of ML models to deception; Securities and Exchange Commission filings from both Google and Microsoft disclose in “risk factors” that products with AI and ML may not work as intended, and may exacerbate a variety of problems, which could adversely affect the companies’ branding and reputation; and Uber AI releases Ludwig, an open-source deep-learning toolbox that allows users to train and test deep learning models without writing code. In research topics, DeepMind sets its sights on using ML to conquer Hanabi, a cooperative game with imperfect information, that requires a “theory of mind.” The Allen Institute for AI releases “Iconary,” a game of Pictionary with an AI partner. Research from Expedia Group uses an attentional convolution network for facial expression. IBM publishes research on a neuro-inspired “creativity” decoder. IBM Research AI and Arizona State University examine when AI bots might lie (in the context of “acceptable” social white lies). And research from Munchen demonstrates that humans are less likely to hurt or sacrifice a robot if it is more human-like. In reports, the McKinsey Global Institute examines Europe’s Gap in Digital and AI. In papers, Johns Hopkins University publishes an opinion paper on the strengths and weaknesses of deep nets for vision, and the Centre of AI in Australia and the University of Illinois at Chicago published a comprehensive survey on graph neural networks. John Brockman will be releasing a new book, Possible Minds: 25 Ways of Looking at AI. A TED Talk from Hugh Herr looks at bionics ability to extend human potential. And registration is now open for the Sackler Colloquium on the science of Deep Learning at the National Academy of Sciences.