May 17, 2019
“Bots” reign supreme in this week’s episode, though Andy and Dave start the discussion NIST’s RFI on the development of technical standards for AI. A Harvard Medical School project demonstrates a catheter that can autonomously move inside a live, beating pig’s heart. Zipline uses medical delivery drones in Rwanda. University of Maryland researchers demonstrate drone delivery of a kidney for transplant. NASA tests a CACADA swarm, and is also investigating Marsbees. And Starship robo-couriers deliver food to students at GMU. In research from Berkeley, a robot learns to use improvised tools to complete tasks, including those with physical cause-and-effect relationships. Researchers at MIT, MIT-IBM Watson, and DeepMind create the Neuro-Symbolic Concept Learner (NSCL), which uses a hybrid connectionist/symbolic approach, and seeming to be a “true” AI implementation of Winograd’s SHRDLU system from the 60s. Research from Tsinghua University and Google demonstrates Neural Logic Machines, a neural-symbolic architecture for both inductive learning and logic reasoning. Two papers compare logistic regression with machine learning methods for clinical predictions; one shows no benefit of one method over the other, while the other claims better performance with neural network methods (although Andy and Dave wonder whether this statement is true, given the error bars in the results). Algorithm Watch publishes a Global Inventory of AI Ethics Guidelines. Times Higher Education (THE) and Microsoft release a survey on AI of more than 100 AI experts and university leaders. The Department of Information Technology at the University of Uppsala in Sweden has made its lecture notes for a statistical machine learning course available. The Santa Fe Institute reprints a classic collection of essays from its Founding Workshops. Robert Kranekg pens a story about an Angry Engineer. And the OpenAI Robotics Symposium 2019 releases the full video proceedings online.