AI with AI

In breaking news, Andy and Dave discuss the Dota 2 competition between the Open AI Five team of AIs and a top (99.95^th percentile) human team, where the humans won one game in a series of three; the Pentagon signs an $885M AI contract with Booz Allen; MIT builds Cheetah 3, a “blind” robot that has no visual sensors but can climb stairs and maneuver in a space with obstacles; Tencent Machine Learning trains AlexNet in just 4 minutes on ImageNet (breaking the previous record of 11 minutes); researchers at MIT Media Lab have developed a machine-learning model to perceive human emotions; and the 2018 Conference on Uncertainty in AI (UAI) may have been held 7-10 August in Monterey, CA – we’re not certain (but what is certain is that Dave will never tire of these jokes). In other news, IBM Watson reportedly recommended cancer treatments that were “unsafe and incorrect, and Amazon’s Rekognition software incorrectly identifies 28 lawmakers as crime suspects, about which Andy and Dave yet again highlight the dangerous gap in AI between expectations and reality. Lipton (CMU) and Steinhardt (Standford) identify “troubling trends” in machine learning research and scientific scholarship. The Institute for Theoretical Physics in Zurich describes SciNet, a neural network that can discover physical concepts (such as the motion of a damped pendulum). A paper by Kott and Perconti makes an empirical assessment of forecasting military technology on the 20-30 year horizon and finds the forecasts are surprisingly accurate (65-87%). “Elements of Statistical Learning Data Mining, Inference, and Prediction,” is available online. Andy recommends the Ellison classic story, I Have No Mouth, and I Must Scream, and finally, a video by Percy Liang at Stanford discusses ways of evaluating machine learning for AI.