In COVID-related AI news, Tencent AI Labs publishes a “machine learning” model that can predict the risk of a coronavirus patient developing severe illness. Unsupervised machine learning on data from the U.K.’s COVID Symptom Tracker, which has more than 4 million users, suggests patients cluster into roughly 6 different symptom types. Amazon Web Services releases its version of a scientific literature search on COVID-19. Aminer.org offers an open access knowledge graph of COVID-19. And “Digital Contact Tracing for Pandemic Response” takes a look at global approaches and results with implementing contact tracing. In regular AI news, the National Security Commission on AI releases its latest quarterly report, with 35 recommendations. The latest Congressional Research Service Report covers Emerging Military Technologies, including AI and LAWS. Facebook rolls out a “bot army” to simulate “bad behavior” on a parallel version of its platform, in an effort to understand and combat online abuse. In research, DeepMind publishes findings on reinforcement learning, with a meta-learning approach that discovers an update rule that includes “what to predict” as well as “how to learn from it.” Research from Berkeley, DeepMind, and MIT explores exploration by comparing how children learn with reinforcement learning agents in a unified environment. Military Review publishes an article by Courtney Crosby, which describes a framework for operationalizing AI for algorithmic warfare. DeepMind and University College London examines deep reinforcement learning and its implications for neuroscience. And MIT makes available online a full lecture series by Marvin Minsky on “The Society of Mind.” Click here to visit our website and explore the links mentioned in the episode.