AI with AI

Andy and Dave discuss the latest developments in OpenAI’s AI team that competed against human players in Dota 2, a team-based tower defense game. Researchers published a method for probing Atari agents to understand where the agents were focusing when learning to play games (and to understand why they are good at games like Space Invaders, but not at Ms. Pac-Man). A DeepMind AI can match health experts when spotting eye diseases from optical coherence tomography (OCT) scans; it uses two networks to segment the problems, which also allows a way for the AI to indicate which portion of the scans prompted the diagnosis. Research from Germany and the UK showed that children may be especially vulnerable to peer pressure from robots; the experiments replicated Asch’s social experiments from the 1950s, but interestingly adults did not show the same vulnerability to robot peer pressure. Research from Rosenfeld, Zemel, and Tsotsos showed that “minor” perturbations in images (such as shifting the location of an elephant) can cause misclassifications to occur, again highlighting the potential for failures in image classifiers. Andy recommends “The Seven Tools of Causal Inference with Reflections on Machine Learning” by Pearl; Algorithms for Reinforcement Learning by Szepesvari is available online; Robin Sloan has a novel, Sourdough, with much use of AI and robots; Wolfram has an interview on the computational universe; a new documentary on AI look at the life and role of Geoffrey Hinton, and Josh Tenenbaum examines the issues of “Growing a Mind in a Machine.”